{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_"
      },
      "source": [
        "# Training a subset of parameters\n",
        "\n",
        "Sometimes when training a neural network it is useful to hold some parameters of your network fixed while updating others. This is commonly referred to as \"non-trainable variables\" or \"layer freezing\".\n",
        "\n",
        "In typical neural network training, parameters are updated by computing gradients and computing an update via an optimizer such as SGD or ADAM. Updates are then applied to parameters and the process repeats until you have converged.\n",
        "\n",
        "As such to implement \"layer freezing\" or \"non-trainable variables\" in JAX, we simply need to not compute and apply updates for certain parameters of our network.\n",
        "\n",
        "In JAX computing gradients and applying updates to parameters are fully in your control as a user. JAX's autodiff mechanics allow you to compute gradients wrt any positional argument to a function.\n",
        "\n",
        "In Haiku (and other NN libraries) it is typical to pass your parameters as a single positional argument to your function (e.g. `grads = jax.grad(loss_fn)(params, ...)`).\n",
        "\n",
        "To support taking gradients wrt a subset of parameters, we need to allow users to split their parameters into two positional arguments, such that they can compute gradients wrt a subset of their parameters (e.g. `trainable_params_grads = jax.grad(loss_fn)(trainable_params, non_trainable_params, ...)`).\n",
        "\n",
        "Haiku ships with some utilities that make it easier to manipulate the parameters dictionary in order to split into these trainable/non-trainable sets as well as to recombine your parameters into a single dictionary.\n",
        "\n",
        "We will walk through how to do this with a simple MLP and teach it the identity function."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gDMGVR5U4401"
      },
      "outputs": [],
      "source": [
        "import haiku as hk\n",
        "import jax\n",
        "import jax.numpy as jnp\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WFp-ID4L4402"
      },
      "source": [
        "The forward pass of our network is a standard MLP. We want to adjust the parameters of this MLP such that it computes the identity. That is `forward([[1.0], [2.0], [3.0]) == [1, 2, 3]`. We will do this for a maximum of 10 numbers.\n",
        "\n",
        "Our network starts randomly initialised so the results initially do not make much sense:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-7B9K2x_4402",
        "outputId": "07db02bf-382d-4ba9-aad9-0f472b307e3a"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "WARNING:absl:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n",
            "/tmp/haiku-docs-env/lib/python3.8/site-packages/jax/_src/lax/lax.py:6271: UserWarning: Explicitly requested dtype float64 requested in zeros is not available, and will be truncated to dtype float32. To enable more dtypes, set the jax_enable_x64 configuration option or the JAX_ENABLE_X64 shell environment variable. See https://github.com/jax-ml/jax#current-gotchas for more.\n",
            "  warnings.warn(msg.format(dtype, fun_name , truncated_dtype))\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "before training\n",
            "[0.] -\u003e 0\n",
            "[1.] -\u003e 3\n",
            "[2.] -\u003e 3\n",
            "[3.] -\u003e 3\n",
            "[4.] -\u003e 3\n",
            "[5.] -\u003e 3\n",
            "[6.] -\u003e 3\n",
            "[7.] -\u003e 3\n",
            "[8.] -\u003e 3\n",
            "[9.] -\u003e 3\n"
          ]
        }
      ],
      "source": [
        "num_classes = 10\n",
        "\n",
        "def f(x):\n",
        "  return hk.nets.MLP([300, 100, num_classes])(x)\n",
        "\n",
        "f = hk.transform(f)\n",
        "\n",
        "def test(params, num_classes=num_classes):\n",
        "  x = np.arange(num_classes).reshape([num_classes, 1]).astype(np.float32)\n",
        "  y = jnp.argmax(f.apply(params, None, x), axis=-1)\n",
        "  for x, y in zip(x, y):\n",
        "    print(x, \"-\u003e\", y)\n",
        "\n",
        "rng = jax.random.PRNGKey(42)\n",
        "x = np.zeros([num_classes, 1])\n",
        "params = f.init(rng, x)\n",
        "\n",
        "print(\"before training\")\n",
        "test(params)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HlQtGLoz4403"
      },
      "source": [
        "It is useful to visualise our paramerters so we can compare to their final state:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "vzv4QNwJ4404",
        "outputId": "c7215e10-9855-4246-ee30-07779c19fb27"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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IjIAgCMJ/j5JEfnwFQRCE5EtS6YvEEBAEIXlhbPCzUyAIgiD87iSRvkgMAUEQkhWKUdL48RUEQRCSL0mlLxJDQBCE5EUSmY4VBEEQkjFJpC8SQ0AQhGRFUvHLFARBEJIvSaUvEkNAEITkRRKZjhUEQRCSMUmkLxJDQBCEZEVS2btZEARBSL4klb5IDAFBEJIV+kZ6PzsJgiAIwm9OUumLxBAQBCFZYWCQNH58BUEQhORLUumLxBAQBCFZYSC/aoIgCMJPJqn0RUkkmYIgCAnDMGmszxIEQRCSMUmlLxJDQBCEZIWBYdKYjhUEQRCSL0mlLxJDQBCEZIWR/KoJgiAIP5mk0hcljb2NBEEQEoiBoV6sf9/CgQMHYG9vjzp16mDz5s3/UgoFQRCE5E5i+qL/EjEEBEFIVhgYxP6XUHx9fTF//nxs2bIF+/btw/bt2/H06dN/L6GCIAhCsuV7+yLg64NSDx48QNOmTVGvXj2MGTMGkZGR353ORE9cPHv2DMeOHYOPjw/09fVhaWmJqlWrwsbGJrGPFgRB+GYMP/tVCwwMRGBgYJx45ubmMDc3V/++cOECKlSoAAsLCwBAvXr1cPToUTg7O/+byRV+ENIXCYLwK/F5X5RQYgal9uzZA2NjY7Rq1Qrly5dH3rx51TjDhg3D1KlTUaJECYwePRo7duxAmzZtvut9iZoR2Lx5MwYPHgwAsLGxQZEiRQAA48aNw5o1axLzaEEQhO/CwEAv1r/169ejVq1acf6tX78+1n1+fn7ImDGj+relpSV8fX3/6+QL34H0RYIg/Gp83hcFBgbi5cuXcf59PlClHZQyMzNTB6ViePXqFT59+oQSJUoAAJo0aRLr828lUTMCGzZswN69e2FqahorvHPnznByckKXLl0S83hBEIRv5vMt2zp27AgnJ6c48bSzAQCgKEqcOHp6v65fp8BIXyQIwq/G533R+vXrsXjx4jjxnJ2d0a9fP/Xv+Aalbt++/cXPM2bMmKhBq0QZAoaGhvH6JX369AlGRkaJebQgCMJ3YWwQW9B/7gL0JaysrODh4aH+7efnB0tLyx+ePuHHI32RIAi/Gp/3RT9qUOpHD1olyhDo1asXHB0dUbFiRdU68ff3x6VLlzBo0KDEPFoQBOG7MNaP+yOZECpVqoRFixbh3bt3MDU1xfHjxzFlypQfnDrh30D6IkEQfjU+74t+1KCUlZUV3rx5o/7t7++fqEGrRBkCDRs2RLly5XDx4kX4+flBURSUKVMG/fr1g5WVVWIeLQiC8F0YfachYGVlhUGDBqFDhw6IiIhAs2bNUKxYsR+cOuHfQPoiQRB+Nb63L/raoFSWLFmQIkUKXLt2DaVLl8bevXtRrVq1705noncNsrKygqOjY2IfIwiC8EP43hkBgARlw4YNf2BqhP8K6YsEQfiV+N6+6EuDUt27d0f//v1hY2ODOXPmYOzYsQgJCUHhwoXRoUOH705nEjn3TBAEIWEYy+kogiAIwk8mMX1RfINSK1euVK8LFiyIXbt2ff8LNIghIAhCssLEIPpnJ0EQBEH4zUkqfZEYAoIgJCtkRkAQBEH42SSVvkgMAUEQkhWJWSMgCIIgCD+CpNIXiSEgCEKywsggafz4CoIgCMmXpNIXiSEgCEKyIqmMwgiCIAjJl6TSF4khIAhCsiJFEvnxFQRBEJIvSaUvEkNAEIRkRQqDn50CQRAE4XcnqfRFYggIgpCsME4ifpmCIAhC8iWp9EViCAiCkKxIKtOxgiAIQvIlqfRFYggIgpCsSCrTsYIgCELyJan0RWIICIKQrEgqozCCIAhC8iWp9EViCAiCkKwwNfx3fnwXLFgAfX199OvX7195viAIgpB8+Lf6oh9NEjkAWRAEIWGkMIj9L7EEBQVh9OjRWLNmTeIfJgiCIPwW/Oi+6N9CZgQEQUhWfH6IS2BgIAIDA+PEMzc3h7m5+Vefd/LkSeTMmROdO3f+YWkUBEEQkjdyoJggCMJPIMVnW7atX78eixcvjhPP2dk5QW4+jo6OAIBFixb9kPQJgiAIyZ/P+6JfFTEEBEFIVhh95vDYsWNHODk5xYn3+WzAkSNHMGPGjFhhuXPnxrp16350EgVBEIRkzud90a+KGAKCICQrDPVi/51QFyA7OzvY2dn9S6kSBEEQfic+74t+VcQQEAQhWWGQRPwyBUEQhORLUumLxBAQBCFZkVRGYQRBEITkS1Lpi8QQEAQhWWHwL/34yvkBgiAIQkL5t/qiH40YAoIgJCsMk8h0rCAIgpB8SSp9kRgCgiAkK5LKdKwgCIKQfEkqfZEYAoIgJCsMk8iWbYIgCELyJan0RWIICIKQrEgq07GCIAhC8iWp9EViCAiCkKxIKgu0BEEQhORLUumLxBAQBCFZYaCXRH59BUEQhGRLUumLxBAQBCFZoa8nP2uCIAjCzyWp9EVJI5WCIAgJJKn8+AqCIAjJl6TSFyWNVAqCICQQfRj87CQIgiAIvzlJpS8SQ0AQhGSFXhIZhREEQRCSL0mlL0oaqRQEQUgg+vKzJgiCIPxkkkpflDRSKQiCkECSil+mIAiCkHxJKn1REjn3TBAEIWHo6RnE+icIgiAI/zU/ui96/fo12rZti/r166N3794ICQn5Ytzz58+jY8eOCXquGAKCICQrDPSMYv0TBEEQhP+aH90XTZo0CW3atMHRo0dRtGhR/PXXX3HiREdHY82aNRg8eDCio6MT9FwxBARBSFbowTDWP0EQBEH4r/m8LwoMDMTLly/j/AsMDPzqsyIiInD16lXUq1cPANCkSRMcPXo0Trxnz57h2bNnmDJlSsLTqSiKkvBsCYIgCIIgCILwLSxatAiLFy+OE+7s7Ix+/fr933v9/PzQrFkznDlzBgAQGRmJEiVK4O7du/HGv3z5MhYvXoyNGzd+NV0yXCYIgiAIgiAI/yIdO3aEk5NTnHBzc/NYfx85cgQzZsyIFZYzZ8449+np6f2QdIkhIAiCIAiCIAj/Iubm5nFEf3zY2dnBzs4uVlhERATKly+PqKgoGBgYwN/fH5aWlj8kXbJGQBAEQRAEQRB+UYyMjFCmTBkcPnwYALB3715Uq1bthzxbDAFBEARBEARB+IWZMGECduzYAXt7e3h4eGDgwIEAgK1bt2LBggXf/VxZLCwIgiAIgiAIvyEyIyAIgiAIgiAIvyFiCAiCIAiCIAjCb4gYAoIgCIIgCILwGyKGgCAIgiAIgiD8hoghIAiCIAiCIAi/IWIICIIgCIIgCMJvyE89WfjZs2c4duwYfHx8oK+vD0tLS1StWhU2NjY/M1mCIPwHhIaGwszM7GcnQxCkLxKE35jfvS/6aTMCmzdvxuDBgwEANjY2KFKkCABg3LhxWLNmTaKfHxkZiV27duHgwYOIiIjA5MmT0bBhQ4waNQoBAQFx4gcFBWHatGno168f9u3bF+uzcePGxfuOs2fPIjAwEACd8jZ58mTs3r37i2k6e/YsxowZg65du6J79+4YM2YMjh07luA8tWvX7oufBQcHY8GCBVi+fDk+fPiAnj17omTJkujQoQNevXqV4HcI30d0dDS2bduGjh07on79+rC3t0enTp2wZs0aREREJOgZP7J+IyMjsX79esycORMeHh6xPlu0aFGc+EFBQZg7dy58fHwQGBiIUaNGwcHBASNGjMC7d+/ixP/48SPmzJmD2rVrw8bGBsWLF0edOnUwZcoUBAUFJSi/bdu2TVA8Qfg3kb5I+qLkhPRF0hd9Kz/tQLF69eph7969MDU1jRX+8eNHODk54ejRowl6zuDBgzFv3rw44SNHjkRoaCjCw8MREBCAYsWKoUWLFjh58iTu3buHhQsXxorv7OyM/Pnzo0CBAlixYgUKFy6MKVOmAACcnJzg4uISK/60adPw4MEDzJ8/H5s3b8adO3dQq1YtnDlzBlmzZsXYsWNjxV+wYAFu376NRo0awdLSEgDg5+eHgwcPIm/evBgxYkSs+LVq1YqTJ19fX1hZWQEATp48GeuzXr16IVeuXPj48SMuXryI1q1bo2XLlnB1dYWLi0u8HZq3tzemTJkCHx8f1K5dGz179oSBgQEAoGfPnli+fHms+EFBQVixYgXatm0LMzMzzJgxA3fu3EGRIkUwYsQIpEuXLlb8jx8/YsmSJTh69Ch8fX3VkbZq1aph4MCBSJ06dZw0fc6X6hegH6TVq1fDxMQErVq1wvDhw3HlyhXY2NhgxowZyJIlS6Ly++rVK8ydOxcDBw6EkZERhg8fjrt376JIkSKYPn06smfPrsYdN24coqOj4eTkFKt+9+3bp/5Qafm363f06NGIjo5G/vz5sWnTJrRo0QK9evUCEH977tatGwoXLowePXpg0qRJyJo1KxwcHHDy5ElcuXIFq1atihW/b9++KFKkCJo0aYKMGTMCAPz9/bF3715cu3YNK1eujBXfxsYGkZGRAABFUaCnp4eYnx49PT08ePAgTnkIwn+B9EXSF0lfFBvpi34zlJ+Evb29EhgYGCf83bt3ioODQ7z3tGvXTmnfvn2sfyVLllSvtcQ8IzIyUqlcuXKszxo1ahTn2Y0bN1avP378qLRv316ZMWNGnM9isLOzUyIjI9XPw8LC1PfVr18/Tvy6desqUVFRccK/FP/UqVOKnZ2dcujQIeXly5fKixcvFHt7e+Xly5fKy5cv/2/6q1Sp8tX8KoqidOrUSdm1a5dy584dpWfPnkq3bt2UiIiIL+a5a9euyty5c5WgoCBl6NChyp9//qk8ffpUWb58udK1a9c48fv06aMsWbJE8fb2ViIjI5XIyEjF29tbWbp0qdKtW7c48b+lfhVFUXr27KnMnDlTmTBhglK3bl1l7dq1SmhoqLJ//36lc+fOic5v69atlW3btilhYWFKr169lB07digfP35UDh06pLRq1SpW3Hr16sVbxopCbf1z/u36bdiwoXr99u1bpWHDhsratWu/mFftM7T3KooS7/fRzs4uTlgMDRo0iBN27949pVWrVsqxY8fUsPjSIQj/NdIXKf83vvRF0hdpkb4o+fHTXIN69eoFR0dHjB07FgsWLMCCBQswduxYNG/eXLUWP6d+/frw8vKCk5MTnJ2d0bdvX2TIkAHOzs5wdnaOFVdfXx/Pnz/HvXv3EBQUhJcvXwIA3r17p1qDn+Pv7w8AMDExwZIlS3DhwgUsW7YMenp6ceKamJjg7du3AID06dMjNDQUAI08GBrGXXqRIkUK+Pj4xAl//fo1jI2N44Tb2tpi48aN2L9/P1xcXJA5c2YYGxsjS5YscUYXAMDQ0BDnzp3D4cOHERISgrt37wIAPD09480rAAQEBKBp06YoWrQoli5ditSpU2PYsGFfjO/v74/BgwcjVapUePToEQYMGIA8efKgR48e8PX1jRP/+fPn6NOnD6ytrWFgYAADAwNYW1ujV69e8Pb2jhP/W+oXAHx8fDBixAhMnDgRoaGh6NSpE0xNTdGwYUO1bhKT348fP6Jly5YwNjbG69ev0bx5c5iYmMDe3h7BwcGx4qZKlQq3b9+O84wbN27E63v4vfV75MiRBNWvoihqm0yXLh1WrlyJDRs24MCBA/G2Z3Nzc5w/fx4AULhwYdy/fx8A8OjRI5iYmMSJny5dOhw5cgTR0dGx3nno0CGkTZs2TvzChQtj7dq1uHDhAkaNGoWQkJB40yEI/zXSFxHSFzHSF0lf9FvxM60QHx8fxcXFRVm+fLmybNkyxcXFRfHx8fm/9zx58kRp06aN4uLioiiKojg6OsYb7+zZs0r16tWVqlWrKidOnFDq16+v9O/fX6lRo4Z6r5YTJ04oVapUUVxdXdUwPz8/xcnJSSlUqFCc+CdPnlSqVq2qzJw5U5k6dari4OCgTJs2TbGzs1N27doVJ/6FCxcUW1tbpVOnTsqwYcOUYcOGKZ06dVJsbW2Vixcv/t88b9iwQWnXrt3/tfTv3r2rtGnTRmnVqpVy8+ZNpUGDBkrTpk2VypUrK2fOnIn3nqZNmyqPHz9W/w4PD1c6dOigjBs3Ll7Lu127dsq5c+cURVGUESNGKPfu3VMURVEePnyoNGvWLE78tm3bKocPH441+hQdHa0cPHhQadeuXbxpSmj9xqT/7NmzyuHDh5WSJUsqd+7cURRFUZ4/fx7vyMS35rdHjx7K9u3bFUVRlGnTpinu7u6KoijKmTNn4qT//v37ioODg1KnTh2lTZs2Sps2bZQ6deooDg4OysOHD7+YB0VJWP3eu3fvm+p327ZtSt26dZULFy6oYU+fPlVsbW0VGxubOPGfPXum1KtXT3FyclK6d++ulChRQmncuLFStWpV5datW3Hiv379WunZs6dSqlQppXr16kq1atWUUqVKKT179lRevXr1f/Pr6uqqNGvWTKlTp87/jScI/xXSF0lf9DnSF8WP9EXJj5+2RiAxhIeHY968eXj9+jWePXuGQ4cOxRvP1dUVr1+/hq2tLczMzODh4YF8+fLBw8MDLVu2jBM/ODgYUVFRSJMmDQBg5syZGDFiBE6ePInatWvHinv79m2kTZsWrq6u2LVrF4oVK4Z06dKhRo0aKFOmTJxnT506Fd27d8c///wDPz8/KIoCKysrFC9ePN5RGAC4ePEiTE1NUaJECfz111+4desWbGxs0KNHj3jvOXHiBFxdXfHmzRtERUUhRYoU6NWrF0qWLBnv869du4Zhw4Zh0KBBaNiwIQBaPT906FCcOnUqjq/c33//jT59+sDMzAwZMmTA1atXkSNHDrx79w6LFy9GsWLFYsX39vbGpEmTcPXqVdUHMygoCGXLlsX48eOROXPmeNOV0Pq9f/8+pk2bhujoaIwcORJjxoyBiYkJfHx8MGPGDFStWjVR+fX398fw4cPx6NEjWFtb48GDB0iVKhWsrKywePFi5MyZM06aXr9+Hat+v5THz3n8+DGOHTuGfv36JSh+WFgYHj9+jBw5csDc3DzeOJ6enjA2No6VhpCQEOzcuROdOnWK95579+7By8sLUVFRyJgxI0qWLIkUKVJ8MR2RkZF4//49FEVBunTp4h2BjI83b97g1KlTaN68eYLiC8KviPRF0hcB0hdJX5S0SZKGQAznz5/HoUOHMH369DifzZkzB/fu3UPu3Llx5MgRjBgxAo0bNwYQ/wKVUaNGxXmGm5sbatasCQCYMWNGrM9inrF582Zs27YNzZo1g6IocHFxQfPmzeOsui9TpgzSp0+PIUOGoG7dul/N2x9//AEPDw9ERkYia9as0NfXh5OTE9zc3BAVFYWpU6fGir98+XLcunULVapUgZubG8qUKQMTExPs2rULHTp0QIsWLb74rvDw8Dg/5g8ePEChQoXija/9gmbIkAGlSpX6V76gFy5cwKFDhzBt2rQExU/IDxLw7fl9//49Xrx4gcjISGTMmBHZsmVLUHr+H5GRkdi8eTO8vb1Ru3btWB32okWL4v0RvnDhAszNzVGwYEEsWrQIjx49QpkyZdC5c2d1oVkMrq6uqF27NhRFwa5du3DmzBkYGhqiTp06sLe3jzc9u3btQp06dZA6dWqsWLECd+7cQdGiRdGjR4849RsZGakusKxbty5mzJiBq1evomjRohgxYgQsLCxixY+OjsaGDRtw8uRJ+Pv7w8jICNmzZ4e9vT0aNGiQiJIUhJ+P9EWM9EXSF2mRvujXJ0kZAq9fv/6/n2utzYYNG8LFxQWGhobw9PREly5dMGzYMNjZ2cHR0RF79+6Nde+sWbOwd+9e9OrVS/3iLly4EP379wdAP7ZaYn58HR0dsW7dOrWxBQcHo1mzZnF2mnB0dMScOXMwceJEhIWFoXPnzqhZs2a8Pm8x6d+3bx/Cw8NRvXp1nDt3DkZGRlAUBY0bN8b+/ftjxW/cuDFcXFygr6+PsLAwdO/eHRs2bEBQUBBatGiBI0eO/N+ySwjaH4xatWqhbNmy6mdf+sH4nP+380LMDwYA7Ny581/7wTAxMUG9evW++wejQYMGcdJz9erV/5tvbVkB376TwuzZs3H9+nUEBwfD0tIS6dOnR4MGDXD06FGYmZnF2VYw5hmLFi2Ch4cH2rdvD0VRsH37dhQpUgSDBg2KFX/IkCEAgLFjx2Lx4sUIDQ1F/fr14e7ujsDAQMydOzdW/C/thOLq6or79+/H2Qll+vTpiIiIgK2tLY4dO4aCBQsiU6ZM2LBhAypUqIC+ffv+3/IThF8J6YukL/o8PdIXSV+UVPmpB4p9Kz179oSnpycsLS1jbfek6LaA0m5zFRMGADlz5sTy5cvRuXNnpEuXLt6FISNGjEC1atXw559/YvDgwShfvjzWr18f50c3hsjISERHRyNdunSxtp0zNjaGvn7cNdh6enrImzcvNm3ahAsXLmD79u2YNm0acubMCWtr6ziNW1EUBAUFITQ0FJ8+fUJwcDDSpk2LT58+xbsXcFhYGD59+gQzMzN8+vRJ3Z/azMws3vQAiNMBfY6jo2Osv8ePH6/+YIwYMSLWD4abm1ucH9/27dvHKeu7d++iQ4cOAIANGzbE+mzJkiWoXbt2vD8Yjx49ivODEbPNXb169TBr1iyEhoaiTZs2cHd3x+jRo+OU6dixY9UfjE2bNqFYsWKYP38+XF1dMX78+Dg/GDNnzkRERAS6desW5wfj+fPnsX4wlixZgps3b6JYsWL43LbW09OLk9e7d++qHaijoyM6deoEExMTdOrUKc79AHD69GkcOHAAAQEBqFOnDq5cuQJ9fX1Uq1YtTj1pOXHiBHbu3Kl2RLa2tnBwcIhTlo8fP8aBAwcAUEeyb98+6OnpoXr16vF2fPfu3cOBAwcQFRWF6tWrY9u2bQCAvHnzqqOdWi5duqTmt2rVqmjbti22bt2K6tWro1GjRr/lj6+QdJG+SPoiLdIXSV+UlElShsDWrVvRpk0bTJgwAaVLl/6/cevXr4/27dtj5MiRKFasGPLly4cFCxbA2dkZ4eHh8d5TsWJFFCpUCBMmTIC7uzuioqK++Py0adOievXq0NPTw4QJEzBz5kxcvHgRs2fPRv369ePE136hKlWqhEqVKiEiIgKPHj3Cixcv4sTv3r076tatC0VRMGzYMHTp0gUVK1bExYsX0bRp0zjxmzRpgtatW6NKlSo4d+4cmjRpglevXqFv375wcHCINw+XLl3CsWPH4k0vEPfH91t/MOrXr48VK1Zg4MCByJIlCxRFwbhx4+LddUFLUvzBWLlyJTp06ICOHTvGuy/z5yi6nRTMzMzUnRRat26N9OnTf3EHg/DwcKRNmxYjRoxQO9SQkJB4dx4JDQ3FmzdvkDlzZoSGhqpl+enTp3inw83MzPDkyRPky5cP2bNnh7e3NzJnzgxfX994fYBjdkIJCgpSd0LJmjXrF3dCiYqKwtu3b5E+fXr4+/vj06dPAICIiIgET88Lwq+C9EXSF2mRvkj6oiTNv7EC+d/k1q1bytixYxMU98KFC8rTp09jhb1+/VqZOnXqV+/dsWNHvPv/fs6zZ8+UGzduKIqiKB4eHsqpU6e++Lxv5ePHj0pwcLCiKLQbwqpVq9SdEuLjwoULyqpVq9TV+cHBwV/dJaBnz57Kzp07E5QeBwcHJSQkRP3bx8dHqVGjhrJ///4v7qjwLTsv1K1bV/H391d69uypvHv3Tg0PDAyMd//jFi1aqDsv9O3bV90hwMfH54v7E//999/KrVu3lGLFiikvXrxQFIX2No7v+fb29sqbN2/UZ8akPTg4ON79if/++29l9uzZX8yflm/dSWHz5s1K3bp11f3CFUVRrl27ptSoUUPdTULLyJEjFQcHB6V06dKKs7OzoiiKcuzYMcXW1lbZsmVLnPjXr19XKleurPTr108ZPny4UrlyZaVPnz5K9erV1R0qtHzrTii7d+9WqlevrgwYMECxtbVVDhw4oHh6eirVq1ePd2cTQfjVkb5I+qIYpC+Svigpk+QMAeHH4uvrq6xatSpBcb/1ByOGsLAwZcaMGUq/fv3i/ZGL4Vf8wahWrVqCfzBOnDihbNiwQfHy8opTbvGxYsUKZfHixbHiBwUFKcuXL483/tq1a2M939vbW3n8+PEXn3/ixAll/fr1yvPnzxVFUZRHjx4pDx8+/GJ8FxcXZdGiRcrKlSuVpUuXKjt37lS8vb2/+nwvLy/F399fOXLkiPL06dOv5jcmPWFhYcq7d+++GF8QhN8H6YukL4pB+qL/liS1WFj4sXzLgrcY4tsGLDg4GLt27friNmAx/L+dNbR8/PgRb968QbZs2fD48WMoioICBQrEGzc4OBgXLlyItXNElSpVYG1t/X/fAdC2YTHb+OXJkyfeOM+fP8ejR49QsGBB5MyZE+Hh4QgNDY2zmGvOnDm4e/cu8uTJk6CdQf6L+N+yU4k2/uHDhzFy5Mgf/vxvSb8gCL8P0hdJXxRffOmL/ht+U4coAYh/wVsMny94A2KfPPn5D3d829B9HidXrlxwdnZWwz//cdfGNzAwwOvXr5EqVSr1sy/FL1q0KIoWLaqGR0dH/9/4WmL2m/5S/BQpUsSKE0NoaGis+KdPn1Z3Bmnfvj26dOkCY2Nj2NnZfXHB1d69e2FgYJDg+N/6/F8t/rfkVxCE3wfpi6Qv+i/jS18UGzEEfmO+ZcEb8O0/1t+ys0ZSef6X4se8E0jYziDa5yU0/rc+/1eL/y35FQTh90H6om9//pfiS18kfdE386N9jYSkxbcseAsKClIaNmyoeHh4SPzPWLRokdK6detYR6B7eHgoFSpUUEqVKiXxvzG+IAi/F9IX/Zj4v9pveVKP/zsghoDwTXzLj/XvFv9bdwaR+AnfOUUQBEHLr/Tb/6vF/9V+y5N6/OSOLBYWBEEQBEEQhN+Q+I/5EwRBEARBEAQhWSOGgCAIgiAIgiD8hoghIAiCIAiCIAi/IWIICIIgCIIgCMJviBgCgiAIgiAIgvAbIoaAIAiCIAiCIPyGiCEgCIIgCIIgCL8hYggIgiAIgiAIwm+IGAKCIAiCIAiC8BsihoAgCIIgCIIg/IaIISAIgiAIgiAIvyFiCAgAgMuXL8PBwSFBcTdt2oRNmzZ9NV5gYCBatmwZ69kLFizA3r17E5PUH0Z4eDg6d+6Mo0ePxgp//Pgx+vfv/5NSJQiC8Hsj/RET0x/t2bMHPXv2/EmpE5IzYggI34ybmxtq1ar11Xju7u6oXr16rLABAwbA0dHxX0pZwrlx4wZatGiBa9euxfns5MmTCcqfIAiC8HOR/kgQEocYAr8Bly9fRsuWLdGvXz/Ur18fTk5OcHNzQ+fOnWFra4vp06fHij9y5EiMGjUKLVq0QO3atTFhwgREREQAoFGVkJAQZMqU6avvdXV1jfMDNnLkSKxevRoAYGNjg0WLFqFVq1aoWbMm1q1bp8bbuXMnmjRpAkdHR3Tq1AnPnj0DADx//hydO3dGy5YtUaNGDfTu3RthYWEAgKJFi2LAgAGoV68e7ty583/TtnHjRgwcOBDFixeP89np06dRrVo1VKhQAV5eXgCAFStWoEaNGmqczp074/Tp018tA0EQBIGR/iguX+uPbG1tAQD+/v7o2rUrGjZsiF69esHf3/+r+RaEryGGwG/CnTt30Lt3bxw9ehTp06fHihUrsHz5cuzZswdbtmyBn59frPgPHz7E2rVrcfjwYTx79gzbt28HwCIZANavXw8nJye0bt0amzdvhpeXF9auXQtfX1+Eh4fDy8sLBQoU+GKawsPDkTZtWmzbtg0LFy7E3LlzERYWhitXrmDv3r3YvHkz9u7di27duqFfv34AgB07dsDR0RHbt2/H8ePH8fLlS7i7uwMAIiIiUKNGDRw7dgw2Njb/tzzmzZun/rhq8fX1hYmJCdKmTYsaNWrg7NmzAICzZ88iIiICz58/R1BQEB48eICKFSsmqOwFQRAERvqj2HytP0qTJg0AMjzGjx+PAwcOIH/+/Jg2bVqCylsQ/h+GPzsBwn9D1qxZUbhwYQBA9uzZkTp1ahgbGyNdunRImTIlPnz4ECu+k5MTUqZMCQBo3LgxTp48iXbt2sHV1RW9e/cGABgbG2Pnzp3w8vLC0qVLsX79etSqVQsZMmTAuXPnUKFCha+mK2aEpkiRIggPD0doaCjc3d3h5eWFVq1aqfE+fPiAgIAADBs2DOfPn8fKlSvh6ekJPz8/hIaGqvHKlCmTqHJydXVFzZo1AQB16tTBtm3b4OjoCD8/Pzg4OODChQtIkyYNqlatCmNj40S9SxAE4XdE+qOEoe2PAKBSpUrIkSMHAKBZs2Zo1qxZop4vCIAYAr8Nn4tWQ8P/X/UGBgbqtaIo0NfXR3h4ODw9PVGwYEEAQOvWrQEAefLkwZw5c2Ldf/LkSTRs2PCr6UqRIgUAQE9PT31XdHQ0GjdujGHDhgEAoqOj4efnhzRp0mDQoEGIioqCnZ0dbG1t4e3tDUVR1OeZmZl99Z3/Dzc3N0yePBkAULlyZYwdOxanT59G+fLlUalSJWzduhWmpqawt7dP1HsEQRB+V6Q/Shja/giIWw5fKzdBSAjiGiTEy5EjRxAeHo6wsDC4uLigRo0auHjxIsqXL//VexVFwY0bN1CqVKnvenflypVx6NAhdXp469at6NixIwDg3Llz6Nu3L+zt7aGnp4dbt24hKirqu97zOcHBwQgKCkKWLFkAUKdQtmxZLF68GJUrV0a5cuVw8+ZNeHh4oGrVqj/knYIgCML/R/oj4vLly3j9+rWajhi3KEFIDGJOCvFiYmKCNm3aIDAwEPXq1UPTpk0xceLEBG3pduvWLRQtWjTW6MW3ULVqVXTv3h1dunSBnp4eUqVKhcWLF0NPTw+DBg1C3759kSZNGpiamqJs2bL4559/vus9n6P1N42hTp06OH78OCpUqAATExMULFgQadKkUUeOBEEQhH8X6Y+I/PnzY/To0Xjz5g1y584da7ZAEL4XPUU7jyUIoJ0U8uXLh65du/7spAiCIAi/MdIfCcK/i8wICMmSNm3aICQkJN7PNm/ejFSpUv3HKRIEQRB+R6Q/En5l/pUZgQMHDmDp0qWIiIhAp06d0LZt2x/9CkEQBEEQBEFIdiRUR48YMQLly5dHkyZNvvtdP3yxsK+vL+bPn48tW7Zg37592L59O54+ffqjXyMIgiAIgiAIyYqE6GhfX1/06tULR48eTfT7frghcOHCBVSoUAEWFhYwMzNDvXr1fkhCBUEQBEEQBCEpEhgYiJcvX8b5FxgYGCteQnT0gQMHUKtWLdjZ2SU6XT98jYCfnx8yZsyo/m1paYnbt28n6N4J110BAOUyRqhhvV1oH96yRdhmKZo2TL32DqUs3POPmxXvIz7qtf+JQwAA2xVd1LA0xtHq9e1/6PmDyvNhIAUtIgEAHR281LDmf9HJhEce8z7I3Up8VK+vv6Pw05OfqWEZe9E95TKHq2HjSwar12d9jAAAQ4+m5HsyUnqCgtlzK+gZ+RgaXX6thkU45OE8zl4FALCZ11MNs8v9CQCw9ryRGqYfU5TX+fTGO8ss1evwqCB6jz77Lerp0U01XLge/qpBh7602pWa7w3n9A6pRfVkm4nz7bSN4jYqxVusdcpHZd5kOz+nZblI9frwQyrT4OOc74njLQAAzXOZq2GGetRW8szkfN0ays/x/0jvbHfCQg3rU5zKdMI2PTUsetcV9do4f04AgMfmdGrY8yBqN5VKblbDvJ+2BwCUXs1l1rQ0v/vqG9plqF0ervdJhylM/w23Ob3M1AayZef27FLnrXpdrgulNzorl1Xp+lQG1x9y2R9tS3XYoJmvGnZkN9dxtUqUxxS9a6th+rr2kKKylRrm1joAAOCwLy2nUZ/Lql0RSrtXMKf3zHNqax8/cno+uVHdRRbl34bCJXnnJfusXAb9CtdFYjDN3jrW3x//2Zqo5wm/HzUOn//ZSRAE4Sdzyr5you7/vC/6Y1glLF68OE48Z2dn9bRqIGE6ulu3bgCAa9euJSqNwL9gCMS35CDmcI6vMcdpPQDA0pFPyzP+m4SMZ0YWvDfXszAq2iEzAGBJtQA1rOMROo67WjsuyEw92gEAtpxgI6J8BRbzoSGU7gcBLJiDIyndHufzqWHN3Ui8ZEwPvNMdftgmLwu+pzeoSIuP5Hva5yFRNmgKi8A9NizKWlei+yN82KBY1ZKMoUbdOV83N6cHAJSYnEkNM7jsrV6/etIGAOB4gst7yzXKY7fKLMYP/m0CAOg0JI0aNugS15vrDkpPdHouq5KVSWSn51vQuslLAECW4UXVsC4FOI/ZUpLwbvQXC77nY6hO8nW5q4adq0f5ifblxVQO2dhQsDQh4e1XMIMatuoh5WHiCTYaqxYJAADUqGKM9+FksLR157J44EJCd2g/Fp2zzpoCAJRd5zhjnaqolxHrLgAALvmlV8Oc+78HAKw+1VENa+2uMwDO8NZxew2zqtf1i1L519IYg6U7UNqbt2SDNaIslUX9ytw26+xhEZ6zPaXDa+Xfali/QpTXwLyc1zzmOQEAuYdaqGEZTILUazPnOnRx+LkaZt4qN4DYAr7OTnq3ZUY2AJ884fa+eDHdP3JlTjVsl59umz7NT4HxezJIjc6+QM2RFLdIWq6Hs74mnJ/CSBQG+nLisyAIgvBz+bwv6tixI5ycnOLEMzc3j/V3YnT09/DDDQErKyt4eHiof/v5+cHS0vL/3MGcvcZHeN96R0nLYBIzOhmMGR66UVBNedzZSeLO8ZSpGpYiFxXixcccMWo/iVYjAI5jsgEAWuRmYZS6JBd81pT0rJm3SNDMugWML0nvLmLBQrd+URI3KQ1ZmGdI8Ub3fxQ+RJB4GnyYRnn1SqfEnw1I7A6YxcbM4yIkjo3Oeaph9vqURhSzBD6R8Bp+hdJVtz7gNpcEp0XLXOo9vc5THl7Nua+GKRlJwK87DlTqS8L0zTZ6zxwAiikZPqU7cx5QkMTfzHpsmNx6zwJ2x9J3AIAThzLrQt5h13MScguu8kmKeTNRevTfvlfDhl4h0du4Vwb0KkhC0L4LzbgYAgivTvlus47F5oiGZBRkM4vCmttUBs/G8mi8eU8yHNNptvY/dY7SqxfF9ZqmMpXz8utA0NzLAIDdrnQqJRoXg+MaSrtVFv5avKljAwAYeZpH+q07Ulv46y6Q1oye/2i3buTdPAWUVEa6d3N6/D5RW6q3nS2pZiXIEGgxMxfCoqitvtMZME+DgFSG9OygZVyf72yzAwCMAtlIa1HzlHqdf1ZjAMDgI+/UsJBFJwAA9pPrqWHKxVcAgFQtcqthAef91ev5w6mcR7tR2/XxiUK9wjoDMS8XdPe1OWKeiPHDqe0Pm8Lf93vvqSyOGnA7vf6S8nj2EYv/NQ35u5hY9PWNvh7pC/yXC7QEQRCE5MvnfZG5uXkc0R8fidHR38MPNwQqVaqERYsW4d27dzA1NcXx48cxZcqUBN1rrnPVGXbFQg17QdoCxbJEoWBGEiKv8rGbxogmJJYeB3JWHgWS0Hj7gZ99cAeJ2wV3UyJmqNLFi4VIjItRJjMWoHtvUSWucgiCxxsS/TG6u8uh1Dh2n8Rh2AEe3a49hMT2ooqch6E2LwAAFfqGYaCublv25jzog0RritE8i/DERycMb3Amjp8k8Wfw6B2gE/CVcnB6D+wgP7OKE/KrYVfHPwQAKFYpcWExpUP/BcWLLG2txrt8jZ8zw4nSM86VRX3ZAlRml/a8B1LSu0uVJHcr+1U8/RWpEb9XXMloGtSNjbQJjXcAANpsaIk/75HI3LyU8loivcZ1xYWFbtcCJDyLNH+ohvXfQQJsU/e7wDaaMtuwyhMAkKZMebVhR2dhF5oPAfScFCZ6MOpbDgDwUrel2wjXlEipG/SvmoONntnNSejmWsTGTDZLal+rq3KYa27KS9kMXI71ndmVaXgzSodBcTZMQnUzTmmNOWzVIyrz4cXZ4Fz38qp6PaE5Cfc6A7nunAbRs01rZMb7d/Ss8bXIiKuQMQJoRadvdnJTb8G2OdR2W/ditze92mRkZMtugPm6Jt2vApXP9BMpsOsyGTMdK7OB2DgH1W3RIQGAzl1p7k5KQ7lqXO/p01Nea+fVzEzd5R/J1vM5bZ4zkCi+d0YgZoHWnj17YGxsjFatWqF8+fLImzdvrDgTJkxI8KmmgiAIwu/J9/ZFidHR38O/MiMwaNAgdOjQAREREWjWrBmKFSuWoHtrriVLyaEsi6lNzUh83H/PbiN9CvE9Qy5ZAADKW7JwfBNA/78990YNcy9Not8h+yc1LIsZrxEYdJme0ycHf77rGgmVzvtZTDoWp7Q1KBKJQ/eo+NqP49H0ypYkksZ4sLgrZEECNCorN4p9t1kEfVpE/toFZlVQw94+pdHycxP4OXffU3p7LWGL8lUoV2H/riQil3a7p4ZFdSgCAFA8ecTVqk1OAMDrMzwr0bgyz56MG0cCt3R3NgTSpaB3bx7L6e5QhFyRLi9/qYZNnMIuNJlq0v99j7DBlaEQ5dHjFT/n2HISvdEWXO9t2vMI/PonVPdNR2VWw54HUb6VctnVsNTmJNiiAUzrQZ9P6P1K/Tx3LQsAwOSSbFx9iKB8L67Pwrtnqxfq9e66ZNlMacltZdIJyo9fGXaXGb2e6sksJ9fNtdV8kuXYa3TP4Rt8z9u5NKtRbH4HNSxXGnpfldpsRBSY2Um93u9F6V1wittS+366WZIgbisjHMnVacOximqYtzdbafnTUPnEzMAAQK5slN411Xg2wWEnzWDULsn53zqOyydyMpW/YWF2XzI1ozQuqciG0p93ef3L3ju6NQQXeS3H5ilsNCQWA4PYP76BgYFxFmMBcUdntAu0AKgLtJydndU4MQu0YuIIgiAIQnx83hcllC/p6O7du6N///6wsbH5oen8pU4WHneNFgvX0CwuXXSfRPjbjyygXpxlgYEoEiiGt1hU+DyjhV6WFeqoYQHXLgEA0tSxVcMmDGRx0jgHiaRlD1ignvUlcaKvx0XUICsJ/Vmr2GC4N4vF7/CrlPZjt1kEPu5J7k25xvACYiUVN5CWtShvDbLxMyff1Djj6/BwpjUUZ682UsMyaYwZP10Z2S9l142CpSkPL19zvLDD5FY0YQavoZg4JUC9jta5E0Ucu66G5ZtFi0qfn+V4K5xJ8FW2YtFeaKFmSsCA0tOoHL/7khcJ0MstOX9lt5Iwj+JoyMkD3giNpOeYGXKEdVXpnlLjOd7HA2cBANWWNFDDrpzjMr01gu5v5c7p/ecVhc2tw4Zmz3VsXN0aTu47pga8PmH2bRKVa1awuNTTuW8dnM/G06sQbrOz7lB+06bg8olpS1v+5nb48Da1n/GNeO3DPyHclqx06yXO+XEdXzhNecxZhvMVoVu0HRKqmYFYygbipxZkTRcpyM+unJGekyM1p3HHc8rPw3lP1LCwuuxOZGxKefT7Y4MaZjO3EwDAnLOFew/omaPrssGuzUPJdPydH2LD39vvwarQsFh/j+2TPUELtJYvX47Q0FAMGjQIALBz507cvn073pGYkSNHoly5cuIalEyRxcKCICR2sfDnfZHvg9mJet6/xS91svC8JiR0m91oqYb5BZHYfP+exUmUNSuMda1ITPVsy4InXXcaqS5ZgYXG7WfkC96yC48ALrnJI9WT5pCP983FLND7FibRctGPxcvTD1Rks/pyvFPeLAinlqZ0HDzEI+zDLtOodJYy/O6TjViA1dpPedu5mUftZw2g68lnNDsJpaXR/e1/8+jplm284NKuCcWd0ZLTmz8NCeYWu9md49gqCwCAVzCXaWRBNmYM79NMSoUFNdSwVrkoPZfS87uHupHR1LQov0/fmA2pKfVJWO7xZHGcPi2VS6FVAWpY2DsSvd3rch0efs51k0J3WTEji/pyjmT4WXZlN6hc9ckAaJCN8/qqKJdf8VkxZcVlZniTnjMEPLNg8IpnkoIjKD/6elzHmcyo3KIzs/DOkI/K5fALTuN+L873PzrjdWFfrve+e+nzbDwoD6PtdwAAxk4F1TCHbFy+kboiGumwTQ0rNp92wlqgGYHf40mFtucufweOH8miXtcaSPl+eoDz9aASfW50lkf8Y9zMru5jy+xTFN9TpQNdb3ZvqoaNdqdE3hmyXg1rtYEW64dpjL2Xmp2GKmXkPCYW/SSyQEsQBEFIvnzeF/2q/FKGwGndYmHHaSxQDU7z1khRtWjnIGPNlpEGun769CEWKqmNaJTSZjoLwgyDaSrlyBP2Y0/JOg2Z6tOo/YxbLEi27qdRSrOc8R//bWJCL49gjxbk1HkJVamjGanXacOS1jzKGxnNN/muJT/t9G14pHW0Mx0esXo1b+XYbh6JevcXLO6y27JgPqUbdb3/nl2ZcpvTO+07c2YjFRr93v8Pi/r9PXlEPFdqMgpKdmK3mlv/kODTC+O6MRtAZepyPwU6FqdM3uvFwqlkVdrZpt9q3vFp4WByI8rsXEANe3WChOe6a4CpAwnygDns0P4xjFxVdt2qqYa9HE+LNVIacn1Vs+ZR5b5/UfkH79mlhh0/TyPNpoaaGZ4tpMLPtglQw5404PI950PC/cobHt1f05aeOf8wi8vpPWn9wtXxnK+nI4+r1zWWUNpHuHL5ZMhA177b2E+/2vziAIBtf/NXs0kOrhunnJTHLlvaqWEVMpJbU4fDPMvy4V6MWA+DgR8ZPreqcztePpkMpGhohu1BZXazaU415MobSmO3c6lwYyXVXVQ+zVaiuSwAAAXTcLsolI3KN+dy3lWpkAW1j2hFD1amFNeIbSIY6v+4icnP/TJ/1QVagiAIQvIlqexg90sZAs3rkOvCidO8CKDb2TIAgMwpWThfus+ioVsH2j7z8kHusEMiSTgZ3uaRy9zVSGBm0LhmXHjO2Q+cSwsyd/Yoo4YZPKVR048hLOBj3ID+DuLR152a0esXIfRM1+ss+DpWofvza8RS4cUsNp/tJfFXbC2nd/g88oeffJPF2ywXWuA6fhQLx73LWfw17kP3vwxmQfyxI/nNz6nCfvH1qt8EAJikZHeXwxacnvBXZABcvlhcDavSj/Kld4t91w87BQAAbGu/wlJdWDkXHt5++/YBAMDKhHeMiTEAXhxlVy6HQZTXg5veI+Qy7Vzj4lZa/XzeXSqDOXe5DcTsW39vH4/e79ZtP3pra3bc03lzTHBkN6rDL0joPg3iWYuYtRM7/uY6POOrmUnyJAMgbPFNNcyiI7mDlEzP5eyyhyzAxv25fAzbV1OvI6OpPeTJxu3ijju9e9xkrodJh+l/vXA2cO495rRt0Bml79+zoXlgOZVBz0GsrFeuojq8diI3AMrP0Mvc3p8EUhk4aoyMXc/IWPT15WfPrkufB0boo7Fu/cesc2xUtipO6bQ243w5ZifDw82b0x2zley9AEMERhjqwvh7tegKP7MHT4Z8FwbfuWvQf71ASxAEQUi+fG9f9F/zQwyBWbNm4f3795g5cyZOnDiBhQsXIjo6GjY2Npg8eTKMjRNmFR06RRuI193EI9q5dBry/AUWXUaa9QCtZsZsX8juHtampCRMG/NhSvlS0/1t8vAswelHPEqoV5IEbJo0LGiajyCBNrJ4DjUs/8qYPd/N4TOD/KLzT+eRzxjvgu2tWdQPPU9ifZ/mcLA5jVmA5R9GPvt6oSx0j+Uk/33PbbwQt+/50wCAd0/Zr/nmW826A3MSfMa1ef96+zw0EttxKpdfzqnk8vNiPPvBRjUrq16n2Etxd3lq1hq0pFHgfpPYMOl+juopvDqPlsdsgwkAy4/ZAwBGHmORp5ylvJbswml0e6R7bykWxLlSBajXHk/omZc8OCxmBidlOb4nqzWVWTM34MFFXflGsKgtXYPS7v2B03hzKn1Rj7zgeF3ycd0siqQ83mrILkjGh6nMm13j0fQPD24AANKm4Z2fbq3hWap770n0D73Ehpt1KWp/LXNz3Vg3o/Y5YAgv2LUfxIukp5Sm0f+3YZrtXItR3bTPy25JJ0aSG9mrEDZYj17XHEJWmPL7pzvX8ZbmZCye9ubva5c6RwAAdivZ9SdsO68X2GVE+a2Thdt7Pt3XavxonlF62z275nMyAOpn4fSePKuZHkgk3zsK818v0BIEQRCSL0llRiDRi4UvXryIQYMGwdbWFuPHj0e9evXg4uKCDBkyYNCgQahQoQJatmz59QcBmHnrhHpdIA2J4iGHWUQWyhtXLGytwcJ+598kblbcYYGWIz2FVbZk0fHnKr4nTRnaxvNaGxZoecaRgClUjYWTU3YSh5ufshB+uZNFust8emf/i+w20aMgib+XmsWem2/TKOn06rxLTT5znimwq0kuQTN28rDo0L26E2gDOA8ZClM63l5mwZi7Lovit+8o3yHrHqth05aTD/jGZ1w+W2x17k+GvHA4z0Qe1YbuFNnbo1nsh0ZS+bV153UFYbrFqeGsTzGmHK95WPeE0ju6OAvGTgepfLUtsH4RNoZe6nZE+tuXhXsOXTJvruayjypAdWiRl9tKwH1+d4zg9rnPxuLVYVSWFVsFcFYb5AQANC3JI9U7Z/GBbfreVGcb9/CsR8whu12OsFF5ojmJ74hoTnfNTdy+OpajQlq1g0f9rcvQ5z7XuXyylovrzvLyOrebbo5UPuum8oFk9YdSHZsZcKHuXkKzLMunc3uef4+f/WgZHQo2fQ63gRjOaWZHhhXjd1eZT+34zgjO46coLt8YYtrIn+XZIHGoyecijN1Gs06jHV3VsMQuqMpXZlGsv5949PtCTEGIH1ksLAhCYhcLJ5W+KFGGQEBAAHr06AF7e3s8fPgQM2fOREREBIyMjBAaGopevXqhdevWsLOzS9Dz8i0/AwBIn4FFp6+PbmFmMAvE7IVYnPgspuFkk3Y8YnuuFYl2b80Ie4M+JAxTN+CRaH3WMAjcRAI8VVveMzybzttIu0h1+QkS9dXLsbgfasOic6HubAFjjc/zzs77AQAp22nK4ROnraUj5We/ZkvRVqVILG7u8UgNO3KSRlVrrGURV6EYZ8JjCPk36xXhEWSDpyTAys3k41pz6NysHn5gazWjCadnbAkSfH/cZqMns+58hZPeLLatTCns77dcFtWzs7jNlYo+n3+e1yKkNqe6TZmS0z2zTAAAoPVUFuDpKrGRESP+U2p3DapGgblmstGyrwfVU7sDLLpDL/CsUFR2Cr84WGMU6ra13H5GDYJ1Ti4X3ztUFvp+LHLT6t79YS+fImzZkmaNPn3iei+YmdPr9Z7KyMyU8x1Tfuc1C3Zz1iSj5p+dPJqeoqpmCyUdMVvOAoDbGXK38tbsrNV6KRkJRic91TDjzuxyl1/nonRrOJ9RkG8GuZ7tqMGCv/IWKp8OpbjMHgdyO738N+Ur+AYbpOnLUx4ONmbxX193OrKREed/tMZQ9P3IbahXobpIDPkr/BXr78eX+iTqecLvhxgCgiAk1hBIKn1RolyDxo8fj0GDBsHbm0dNjYyMcPr0aQwfPhyWlpaoUqVKgp/XrDQJwRg/ewDwnkw/yEO3su/+6hsstix7kwhyb8yj3M1060y937PoWPJHjNAIxuQrPDIaQ1BjWtBqwFoKjybRmoVsf/ACUGUTpcd9E2Dcm3zAs1dkEeM+n0aqzZuyO5HXPfIpz1uCF49mncCnvG6/TMZOanNOb4juVOK6C1nAT7lJYYYPef//GyY8CxDtQEIvcwnO31+6BaIpDFh07dCtadDTbIvaUHO+QukypIpNurDhohdKovbwABZ3DQeROPZzP6KGLbzaTL1uNpf+Nz7JB675NqeZjhv92f2m9CqdYVMAiNJNjgRq9sQPTkv5XluNDYWmJ6kM9N+wQB91jQRotszA2R4rAQDWJWqpn9fsQGU18DIbktd1dtZgO85/g2yctj+sqSwHaGYq3LxpRmR/2pxqWLju4+xpWfxPL80CP+bwtP3rA9Sw52/pOcG3eIHqh1LUViKK8ZqXSB82rmK2Ke22pgS/5xZ9X8495sZrfJB2H1rowgvQI6I5X/0X0nMMcnD7GWFD6bU7yIbmx+O0kHuLERvQIav5YLeIKhQ+sgcbe7PWkYtR1VWacwK28nek+UoytIYv41kdrVXeiycHvg9D/a/HEQRBEIR/kyTSF333jMDOnTvx9OlTjBo1Cnv27MGVK1cwc+bMWHHmzZuHV69eYe7cuQl6plfwAQDAh3AWBY0nkTJs3JrF7aVXPGKbUrdI8cW0O2pYWGOaHfAaxuIl7zJyn8iWnQXJPxr/+4XTSPyM0uwxn083sP7Ai4soYgOJID3NiP7h4+wqctaH0lYvK/vI2FankeMC0/lgtTO9NqrX6RuQL71jWxZg9wLoOVU1Lk2rdtEzo63Y6Elx4CnncRgZLE//YKEWlYdGYqNyW6hhaXUHm2lnRII0wvthD4qbew4vxK2qmwE5x8WMXa1o5LjpOs1hUJrWpPdO50LUlBeNbr5EorVcEX75nLIkHKvN4LrJXJrL4vV1MmLq1uf3XHhKcQPfcT0Y3SEXmGZ9eDZhx052AzsxlhK34iGXXzrd4vHb77lNXV7Nhq2eTqzrfeT3RNnQjECo60U1bMQOOmfh+GtO44PLbKQ8HE3tt84hdgPLpnMJs8vKdTzmMJWV0Q2eydDTLFZXTKj8GvZhNx4XOj5B3fYVAKwbUeOtptl69Io/10Pp9BTerQCnsfYaavtWWdgQfzuDzt/we88Vb2SoKb+yZOjvXMSzMHfe0/2t83A9FGpH6wqWzuZ4vcezYWJRm2c9rrWuisSQz3ZFrL+fuPdI1POE3w+ZERAEIdGuQUmkL/ruGYHDhw/D398fjRs3xocPHxAaGopRo0ahQYMG6ixAw4YN1cN5EsIsnSvK4WMsXhYMJsE34ACLxCy8HToympCYihjBC/m855EPcpuyfM+KRiQ6KliyQTEyLY+61tbtCT9bc7BR+hQkwEKfsGDRL8QjqP360rPWakZiDz4kQTl5CYu71P3JAOhRgF0ubndroV4r7zluDM8n0Sh61SXsqpSxOInjxvk4/oZtLBIf7aMR2LqTeLvOngUp7d2Os9BdWJNGfnsd05xQPH25et2+ADVW7cxDl7Yk/q4+YUMp5lRns7QsbovwBkGYUoqEd/ZU7Eqy8QzFXVuV66ZYByqXIWNZOJ724ZH16JJUzq80LuhTbMk42PSM01Olbsz6jGjMP0n5NbnAxl5Gk5wAgO3dL6lhRtlIMO/fxPXapj43sPyZKQ+vA7mOg3WLvsc583am73RN1uslp/tIP25Lax5RenfX5bpbdI/crBpk43imDenZI904Xu1hbGieHEVrPipkZEFdqyXds+8fbs/Hr1E51yoX//7827rTtryDzrO7UMAiWvyednJnNczAgGZPrKrZq2F31rDrWZ0DZNDNu8dt4NpTCmucg2cE6vQlob/HE/D9SD87qWvyd/GQo+aQwMSSREZhBEEQhGRMEumLvtsQWLt2rXodMyMwfPhw2NvbY/fu3cicOTOOHDmCUqVKJfiZc8uR6HgVyska2pNGEo0AZOxBI/1zKvNWmBd8dSPnRTW7Cu2irRxzp+bR4A1PddtNBnzE/GWkKCPz8MLeW2/p/irWLMBifNIN7/qrYXdceC1CEzf6vE1uNhT8c5LAfZ6BheWTiyQCV2Vi0VqMPZ3wPpRGat2e8nB6nolFAQAZTFj9hobQ+6pnYnH3eAYLuTMnKe7ha9z4XBdSWSkmnMa2b2NGX6PhqjsQapsNi7+waDIurpTlMww6bad3Z7DikXzPe1xWOzrT9ey7LO56nLEAAKy11Rx01YHSVnYDxxs2jg2AlTdpRL1kNhaWN9fSeQQhLdjA8c5K5XxpAPuR3MrPRlO1AbSe4p/cbCA2OUn/G+VhYZ2jO7nOuL/m8vn4kevhsgfNBDTnnUDRoyCVs5UpGzgORyndZmZ8r/YoqvsfKG6tHTxj8PEQzRR9HJxJDbukm1Gy7pwK/W3IQIpUuL69x5OrmMcbNgD3rCSDbf1UNkJOT6UZhd5HgBpjKY/nn3C76LmuJACg4nSe6Ri5pzUAYO1QXpcS3oQXrRufovTu9uQ2aZuNvlebD/FzKlWn9lxqMKc7yprL6vwgypftRs0C6jPp1Otj7DX3fSSRH19BEAQhGZNE+qJE7xoEIJZrkKurKxYsWAA9PT3kzZsXkyZNQurUcX3y4yOf3RoAQOEhvAVjJt2CypypWGjsecxiKubgz3ereXecfVtpZNRuFS9szZCFhEjlnPwc7VoExxwkbiadYPcJA91pZdotRf10e6w712DDI5MZC7BWuUk873zOO7mMb0nCaucxFrItWvLnMW47aWuw8I5J5+EZvCA1OjuN4OsVYeEc/ZBFtl44ief1E9gH/oVux6KUmkO0Bo+ke8r35JHvKwv4bIKUTWlYP6sl57t9HhJvDbKzoKuxm0Sre1MW7b0u8D2d8pK47jmSfeVjfPqjG7FojwyhvC5uwcKxbEYWur66RbBL7rMhZZuJDA93zV71gbp1FXlS870umgXYoZ6UHiU1l0/Z0tQGXrzjL+zb9exuVXskrfU4OYa3zDxzmIT7BM12nDH78rvacdiWZ+xiNLkH1ePe3Sz6Z92muGaaRdBzy1M6LvuxYZIjFZdvJ3cyXp+NPqaG1VxCbkl3X2q2cdUtWv6jDj9nyDF26QnzpbLWD+IyD9l3CgBg2q2BGja+IZWld6hmdu0UX29sTcZ2197sljTmD2rHuVNzujsuo7RFW3B93ezD7cJQn7/T5kZ1kBjyOqyL9ffTg50S9Tzh90NcgwRBSKxrUFLpi37IOQJNmjRBkya0yLF27dqoXbv2dz3n6j4aqT78gsWLtSmJpFcaIRIWxqLWoSAJ8gv9eEGvw1DaSebsnxyv2nwSfweu8CyB754d6nWuHV0BAIoXL6qN0FlzfulZpHgOYrE+/y7t7DJ+GRsFF5voRHZGFsRdVtEo7qL7LErDGrAQjllvoG/A9+TR7bVeYUhONezyBDIoojTrEyq3Z3eQmJ2Ktv7N+X4SSGJ9ZWXe1UUvij5Pl4IFaKn+/J5rq8idZuMaFo7ldFti5l3DMx2OBeg5wZE8QnxpCZffFU+ajTDpXVQNC/7zHABgXwtO9x93SBAPGsppHDOV31PYgvJ7aiIL9FO6ulE0FvfwOSyy/xhGIjyyJNeXoc7vfvNq9q9vPYGEcIaamsW5moW6iypaAAByv2PDbZdnTgDA2zBuky/HXwcAtDXlQ9jGlWCDZL/uwLGeZ3kWKmaHId8n3H6CI6m+Hvmy29aWegHq9fxKVKZ/7+cfqFETKW3zpvA9uz3JCPYOjX9EQu8jpU0vkN997DydL9G8PRuFp8vSbMKc8jwLt3Ye1/fEgjS7Mnwml8WMTrQd6bu3vFZl9oGYhedhKJKW6nPjUzYKtj7k79glPrLg+0giozCCIAhCMiaJ9EW/1MnCtXaTICyi2Xbx3A5ye3BoxwLqRDMeBfcKIgGyqMVmNazGCnJz2fKMXVda1qcKaZOHBUu3ir3Va2tTMhCirHnUuXhRitslH/v2511KbkKZsxgAIPGybTiLKWd3EvuHzrMYT7GHBHyuieymcqEH5+F+AL3nRTCPoJ7yIZE0shgL6859yKAoYs3xngdyFe6tQ88s25qfHW5LLjITzVgkHlhBBkcnVzZM7g1dqV4P2t0eAPAyhMsvRhx3PcrlY6rbCnO/RtCFV2Z3j5Mr6TqDCY/8zrEpDwDIn4bXLDjodum5ZMuLu0/yYDqa59JtIatxrSrYnuJuq8Ej2k8+UHpbuaSGfiMSsC2Ks9EU3YDKom0XnmVJ145mafJm5DLVL6XZnnU71b2JBRsUV/3JqLw9jYWu0190gNemLnwWRmNnHtnuW4XSmVkzun9HN4hudI0XBl+1pDS20mzXufIRz2zt7Ek7DMUcvgcAxtXJyFjxiH907rsGAAC6D2bjUtnKLj/6ulmoyCJsFPl/IoFfahjPXJ3bQu294io2aqr34IW9p25T+f7pw0I+y1hq572z83M26U4tzmcejsv+VPeVrfh7U8yK6ynRGCSNH19BEAQhGZNE+qJfyhCIcfP5J5iTFbP3expjFlAZTdh1qEJ/2uLTfnUnNeyWbkT8ljuLi2p1SIg07cguDBk6WajX+56RkFnVgkXr8odkmEy7xAJ0Zn0SrTMv8Wj5+Bssft+eogWSjxezqG1SnIRRv8Is6qsNZWEVmZ/eo/+eZyv2DqC4jj15JLb5cErjqOJsKDlfUC/xTjdTEl6VfeCNLtKsRa6qPMr9MZIKekBJNnBWLOHV7MXT0bsXalxxFN3ZA1Or8T1zbpNgfrmDF+QaRXA91TEg16MqmgNZvXXrP0rY8i40+w5SWfWtysJw1RV23zmZk0T0lrnsdlMyAxkfm5/y7JGNzs18aFUux1mTeMHz6/O0K1X7LT3VsOO6dRVLa3FbCYpg8VwuI7Wbg+V4O9i/gyidTmu4jgcvpedculRODet7kZ9T1ZruefSB27ahEV17XWPjYcqkdgCAhRvYwNk7Ur1EG1cyAI684PKJWaB9fTsbFDkakVhvXvOgGnbmIs8i6LyxMPUmG8bjL1F9vvHn9hVzgnNfzWFi44eyIaWUoM9Do/ieFTpXsS1/s4FYQXcWh6nmoLPVj7h9vdiu2Uo04TsOx4+h3tfjCIIgCMK/SRLpi34pQ2BudRKgw87xiKx1HhI8m9fygl33VyzuDv9BYqNRHc2+lkYkbtL3K8L39D+tXrdfXREAsHUDGwWKzgo5mZXFiccNEus3+7ErRPnqLIJmbycFVt6SRf2C9GQU3HzL6TXUp/z0HcYj9S2H8Ahzt/yU71ZHedbjku4AK+u2LEArZKR4d96x6FpWmUeLi7UIAACsWMjVuqQoGQUbZrPQyj6RFPOUhZyv4X3Zcp16gYycRbXYKLrjQ/nqt5oF85Ju9Pm97LzQc9kKFowGN8goKl9Ts7XkOxKCnjk47PEHqq+85pE47UP1Pb1WXB/5g/+wsHwfTuUbHMlCdplmW9A9nXcBAAbvcFTDIhRy/1p3jPMwu33cJTLF0/Hnz4IoP57BLLxT6F45/gy3FcPc9JzmR7kc/a4GqNfDIqhuwzQHju1qSJ9vKNReDeucnwyGJ46cl13P2bhy0G0Huvc5j8C/2k/TJ0pKnmV5ueoZpbUN72w0U7Ne4tEbaiPHHDivqx/Tu/s4sdFYfS/lf/GtVPDb6gkAyNebzyZ4ojvNW7str54euXgVMNccUjeEdxAaNYvavvbwtVo9+PuQWJQkMh0rCIIgJF+SSl+UKENg3759WLGC9kmtVq0aRowYgb///hsTJkzAhw8fkDFjRsybNw9p0qT5ypOIm+8oObkzsNDdVJ3uzfOMR0h9/uKFwfVv0Khz6n68R//U6iReJmnWe6XoQ9u+7G8ZCIBGjHcVYwF7uQMJz7M+PCp9VOcmVGMXp7/KbBqRdem8A51q0Raf6042VD/fvoLEfoZ+fE+/QiTgdzmzD/vZVyzKmuSg0dJ3B/k02ZSlLAAAhhqLst9uEsLprLjaPCfweQQV/6LR5PO+7Fbyh26P/g2arVLb5aV872nMot37o+ZEYJ0mm3qL8/BsDAnrnps5r+ufUh5evufGrqcxgHJ3JCMmd2o2KILCyWjS92cjpP8OemF+G82J0ZqTZtdWJWPnYxSLydRGJCLn3+NZguWVqOzvvDdE45O04PVBAIvNfTo/9KcjWGQHRZCBVGI5G5/6mu1c69cmcf0unNOzzZYWa/81hw9Ku7WK8lCq+n01rM1CnrnadZPEfBPNuoFumvUCMVjq1sRUs+L6aJqLRfLCe2S8vjyj2W5Tt4alQ0s2lEYWI5cfFy8u+7F/8LVZRUvd8zg9ITqjqmAndiE6vZTK/lMUgNrUHiKiA9TPDcjTC3YDuT4jKtE9YwfyuoqI8vQ91YuKxpRtMelmA+ftn/xOnLVFojA2+HocQRAEQfg3SSJ90XfvGvTx40dUr14dR48ehbm5OVq3bo2BAwdi8uTJGDNmDKpVq4Y5c+ZAURQMGzYsQc8stJpOtDUzY/EbcFy36DM/i/a/2rF4qZGJBFxD9q7A5FIBAIAGlQ+oYRnyk2LJ1IvFmc+fD9Tr+660n2fh+tfVsAv7SUzZbrVQw+oV5lHOAxM8AQDRmsXEiKbi1H+lWXRch2YOilfkeOHRnMfOeUmQZ9P4jxe2oAbk7s3VM2QAiWz7Eez6s9+Vy8LwOgmvuX+y3/eUi2TMvL3OLkYxIjxrU941yMuT82W8idytHlzkPTNDIqke6u7nPIwpS3k88YoFqOsDbvghvmRU5S/J9zTKTgbXssuadQWbybArO5br5up0XhjceAqVH5uHwJbOtGuOiVN1Nez6eM5DE1cS6y/Xe6phk2dQ2BkfNjhGF6eyn36LR/e1RCtUTwXScDm3yE2GwqF/+Dm7vci4qJOZBfGqrmywtl5Oi9kffOBR+0JpqHw2XmKj0GAHCeJwB15Mrp2RKjWS2kgpB/4+pNcdinbqHhtk2XUj9J4beOFvdBY2mozO0YnBjy/xwv4uZ2mRfe3MbAhNcCVR37EcG8jrh/Mzbx6hOltynw2XOlnoukAaNnRGe/DnGXSL1EeVYOM0X79n6vXfi52QGHL32BXr779XNPtCTEGIH9k1SBCExO4alFT6ou+eEYiKikJ0dDQ+fvwIMzMzREZGwsTEBGZmZqhWjQRkr169EBgY+JUnMREHPQEAbwvzjjEzx8aM1EbC4w2JqAF9eWS45XgKe36EhXdHLxJJPo86qmGFe9No+6uDPpg+gkTfiDp8+tXNtySCPA6y33epimQoHD/Fix7HXeeR48gCJCwzVeftPJvnp9mGtTdYrOfMSAKtW34uiwEH2aVnyNArAICic9iNI4bHz1j+lh5AYnP/NTYOxrXg68OVKD+DD3PYzW4k4OoZW6hh94eT3/jbs0D9lW0oj71ZrBfwoefYHghQw/bXIyH3IYDFr4sX37OjPZ0rkbEpb/myaySJ0e7H+Z6toZRvt1a8Q5BP45jFp0Hoe5bSGVmE28CBO9RMzc1Z6C4/YgsAmH2Txe2u5+xOlFW33WyPGVw3I/eT8fGkP5d9b912p6dXsn99ZCG+J2bVfxF7LtOWx0jgptQYrP5vqZ46VOf1CSuy84xKzA5NWc3YWFnrTuVjrHmOcUfat98YQMRKml0o5cdtct4Aau8LNKK/mjW9020lG7b/ZNCtOwHQdRa1xRUr+DsyYj216Xw12WWu1hQyPmJ26gIAbKZnrt8MROkO00vdkc/SOKLb4WtlXzYODo2gXaK8rnB73zeQjdxQ3RqVYVfYNU/fT3NaXGIxShrTsYIgCEIyJon0RYk6R2Djxo2YPXs2TExMUK5cOdjb28PFxQXp0qXD/fv3kT9/fowbNw4WFhYJel6lPbS15JNRu9WwgrNJWHpp/KRNtrH7xcDVJGg2a3ZW8XHRudhoFq6eX0Piv9wKFmfZc/Lo9TzdtozNtvLIcI+qNAq8ajePBvtt3AQA2H+hLcebpBExuqkgxYRtLEXnVK4cvKmG9VxfVr1evSgAAJCuHrsOBSwjAXZkL+/QUr8diedC/dhHe0XlAPU6ZgFozdUsjrPnpnQctGMRmL8YHcJl2pX3i/+05oh6bbfcAQBw+QkL1LBb9O7pA3gkf5cXlblvMDf2l6dZ4GeqTAaZ3xoe3Y/QLWRe3JpHmKddpfROLM9p7Nee1zSk60uHptXPzSPVg4tS3Rrqc3rCoqgObUpfU8OqLqrFadOdDvzqJbeLdhWobseU4Hov3JvfbapzoQl5ye/OWYoMspfrnqth97aROLY/zm2lZwHOT5huBmh44zNqWMaR9QEAtfPzPbsuU1upXZK/lhNL8nM2PCHjy+8Tt91q1mSkRWu+ycP2kMHg0okNk3dhXJ8DT1CZl8jFov/iGppRen1qrxqWdQztrPWgO39vvIJ5nYzddgrvVJZH/A/rDMQXd/jdxhnJGGynmVl4pTnHo0wGvr9HwcSdKJZrwL5Yfz9f0DhRzxN+P2RGQBCExM4IJJW+6LsNgYcPH2LkyJFYvXo1UqdOjaFDhyJ//vxYuXIlNm3aBBsbG/z555/w8fHBzJkzE/TM/hfpQKOAcBaWWXS71WzdzULM6BwLtSOHMgMApt9i8ds0JwmQoml59NV2AmWzXhOOd/Iui6mo6+R2o+/NfvN71tHIsHb3HPdZnup1RBUStTkKsxgtZ0mC5o1mj3m3G/R/RkvOV2AgF/vLaUsBAA/utVHD9uncTrw0OyjF5Kvtn2oQLo5jIbfPi+55qNmZ5o9yNINRqOvfatj15STe5mnyHxTBabv8mkTkq2ssQI1zkPgdpRnxjlnE220mi7vo1Oz6klX37hKaxdT1slA99lvP7zZ4QIu/c7bProb5+nK+rKwobX+7aw5PC6Z3tu3CMzS1M3M6uu2nOkubTrN49y7V7cwOahC8dWsR/D5xvEbZua1ZmlA6QiJZRDfppkuHHofNnEOj5fbZuH0VnsDuWIruIK0ZTTiNMTsInfPlmZWppQMAAAPPsPDOlZ7Lwkd3nkYazRkQY4rTyPvQSxacr9m0fiFCs4NU52ZcNzEifFZZbu9X31AZaMcwBrvpZhY0gZolC1hehcpitAfXw30/evarJyzuYw67A4CMBciAtE7L34FCGterP8rFnRn7FnINPRDr7+dzGn4hpiDEjxgCgiAk2hBIIn3Rd7sGnTt3DhUrVkT69CSWmzRpgv79+yNnzpywsaH9Ih0cHNC/f/8EP3NiKRIlpaZwsvYM1O1K0p79qD2d2Jfc0pQERnVrFh3jzpIIfPdQs4ONO/le13YuqIZd+JsXjaZtSCPvHz6wwDLSJyFnqMeCRf8NCeEMw3hPTGuNb7+rbgHttTaahbbFaQQ1lRE/R6OLUHou+fR7vOE8bnlAYmlGJXavaD+NxFKGSuy68jaMxeay6yQoAy+yy4WLK72obHueWZh0gwykM8/5fSamLGpjdnMZ2ZbFupUpuYDYaHbU6aw75fbmXDYO7A+zqPXeQzMziiOvRTg+gGY6LIfx4u569qQyJ+kWSAPAtTee6nUK3ZaTQaU4jd0OkvA++owV6uCiJOCNDVLjZle6p507l7ltA91JyD78nC3t6fyJSftbqmFtR/MMT5m2pHqXVgzgtG2j+tLT43Y6V7dp1ZBtXBb3JvIslbNuK9GXIVymtTNTmz31isus9XKqk1ylOY0tc7HL09BJZJylbJ1ZDWuxjO5pWZ8NmFGuZAAcfsHlM8iBTyPOOr4RAKDkUU6P4VFa01BuTgk1bHtDal8B4ZyeVqvYoDCvQTMmQ4tymzPTnWI91ZKNolK6hcHLrpsiIoI+L5aWjaKtKwPU6z94B9bvQkki07GCIAhC8iWp9EXfbQgULFgQs2fPRmhoKExNTeHm5ob27dtj3759ePjwIQoWLAg3NzcUKVLk6w/T0f2cBQAg2pLFeIvu5HvsvokXHlZZyz7nY0tS3P3/sOgqk51ER2AmFvq3c5YCAJzxYQU+tjILrOHrSJyY5uB7RnqQmC9swYIlKi+lI2YrRQA4spkX5/Y8T6LO/jgL+CfPSBDVLMai9Po/LMCm7SNXnPKWbMxEhFPcno14EWW2iZSHmllYbDo5vVavq04hA+jMTh7Jj1nIfGUQu6TMOkun3xbUHOq16QnPeuxoQKO8Sx9wWcztSW4wUZpF2617UXqrbucZEYDzaNWYDIBJ5bgs9i8gN5+9F3kE+EF6SseSB7xrkutrHmF+MJEWL+cZzycUp0xJ7+lQlEX7OV8qU+etbKwsbMV1128PlcWxzmwgdr5EC1NHXOX2E1k47tei9GzOY6PaJLzTm3BbWn9A56pkyaK++Cq+f7fufArtzEK7eZSHjGW4zLb3pHJpNY2Fdb6K3FZMqpFBN6NMgBrWdDatb3DNy777e65TGl0052Lkm8nTks5FqQwOZuZ8n/9Ia0PCovjHq2EncvUycMiphhl58HoAp5OU30Jp+Dn7/6A2OWo6ty9/3YxL0az83X4WxIboqgmaBfeJJYn8+AqCIAjJmCTSF323IVClShXcv38fTZo0gZGREWxsbNC/f3/UrVsXY8eOxcePH2FtbY0//vgjwc8sm4FGNJ+kZdE1aT6J7Au+LKAyZ2ZhNPE6CbBMmkWY88qTiJx0PUANu7DgIgBgLwCjXrSY2c2UhW77xiRq62dlEX34BaWjVyEWmzt0jtiKsYFqFNTawyLozRMS6YY3ePHp3Hk0ej3pvGbfec2uUtNPkGFTpAWL45hR+b0neEGzve7QqqqlON6GljzDMbgoib7RG9hoanmI8hjcj3cAilYonnZ0v2luNor26/brv/GODS7roWTQdSvE8Y690m33ypMNqJOZjZQDL6lctAd0xexylCYHC7+KusOmwqP0sGQZlX+/3nzPvU9UN09Gs++/fs+SAIA2mnUDPS9YAADKlgUaZKV09N/ITXx/bxK/i+5zvedJTWUQFcViPE0GvufP8gEAgMpHOD3BkSRwm1qzkbFWk8cYDNbw2Raj8pDx5fdW44mn0Gh7WBiHxZSV4QM2BBoP5HaTojq17W4nLdSw67pZGJuZXPaGN2lBvXlbnpn6Z7y7ej02F7lhrfiLF2V7VScj74EXi/WzW2La0gdUWEDvSd8sp/r50z/odOXa8/m8i6isZPie9uHvsafmBOzNNcm4OP6SDYWuc7ktPp+LxGGUNLZsEwRBEJIxSaQvStQ5Aj169ECPHj1ihRUvXhy7du36wh3/n8pWJKzeF9SuEdC5BqVkcTItVLM3/J+0wDGyGG9FWNSCfM63bGRh1HoVHSJ24gmLj3I5WHxs3EVis3gPrrgjjynu1h631LBjp2jUde5dFpPHb3HaMuQjsfTmE7vvbHpGQq5wFo43vgQbHPUWk+B+oXEbOdCMRGKfiyzqK1cioydrSp45wCVv9bLJGhKPl8+xKIvUDVqHvWBjJsbNw8mWZwmyTWTftTfXAgAARnnZEIj46xLl4TjP8ExscVmXfl74PH8wr9+Ibky70Aw5qElvfspP+vRcx4u2UL3b1DRHEUcSjykNNfvSR5DxsfxQSTWs5zp65p/32AgroXM1uehvgl2eVD9HnAPUzzc+pbpx6e6qhk3aTQaSlyeP7ut/4PTmLUSb3tuv5dOIa2SidlXekmdHRrej+tr4mPOValpx9frJQlowHVmeXXpS5CdRn5fXiKtrFnyenFPDru/knZjsatGCkywzS6lhXsE64/M259W8KbUB25FsUJiYcnqLOJOBOeKcZkG4ziBJlZrz8CKErkukt8KTERRWqP0TTs8UWqx/9BV/rwo3oHK+OJXPBojOTN8Bu16WmHWbro+s4rTdWMrfp8SSVA5xEQRBEJIvSaUv+qVOFu40jMRx0348WvznPRIN915qTr6txq4dVVtYAACuv9G4gByjewIO7VXDtlk3oYsoHkE+F84jlqEubgCAYZ945Hy2bnnD8FK84HLCDfZ7fqtbEGxhwYZJexsSZfOestvDy/cktiI0i6DdrVg4dbCjzye6saiNciNBrRfOawACWucEADjUf6GGGXRhYR6Wj4TezudscFhmoHcG3uRZhIHnSIy7XaiqhnU/pV4iZSEaRQ4O5udUmk/nMLSYzQZM6sFkXE3XuKn0GsH736+qQoK6dB3NQWDlyEBys7dQwxrq1k7cOcvPnjyAhblBBdqDv/dsrmOj5/TMTUFscJWqS+k2MVAwuxylyWkfv+fjgtsAgAOnK6lhrerTiPaSPexWM+8uuyVlyNcLAHBjMx+OtXopfb7hCddNSCSV88YavKA5R2p+Zq7HlJ+3c9epYV4PyS1JX4/byrIH9JXMNq6zGtbJTfNjkodG8IfasMvP1JuUHtOGPPrfuQS1w6tZWPxX6stie/tzeuZOO97lad5d+t7sP8TfkTYbSazbj9IYXF14O9MLuo2TMmXg78C905Q2/RxcjhY1rdX4OXQ2u6I5bCVTXj4Y7+M/9kgUSWQ6VhAEQUjGJJG+6JcyBCLK0NDojh4X1TD3szqhWxrY8oyE+4Cp7J6SyY4ERpRm6/NI3R8283mLz1e7eKS6dCd6z5UzPOqcyoz82bt0YLHk+pqESqYG7JqhPQugy18k4G3rskhaezPGiGExlSKFnvr/jto0W1HhDx5t13uny49mFLz3KHKJss/Go9NOje7p4ukjRVc64fjjSfarbzOA7mmcg2dCYnz/DS/zWgLvEDIKHI4DxZvSPVvrsIAtVfokAGDh4fpq2M23ZLiYFWJxN8OWDLKLfob46wEZSA2zcR5GXiWBqz3IyjojlUXO+WwcbG6ju6cYzwDVa8DptRxAbUC7b3//wpSeod053q1HLGotd5JYNTfne0KyUdpHeVioYcM3kWuVdyiw8BLVo4EhNyb7gmR87NzJ9ZDCgJ6z6QnHe7WF/OYXA0jVgAzHp2Omqp+33twVAGC1s50aVqEWjay3XcTG0xrXmB+OSFjm0O3edJMN34y6kf7tf7NhN6QoGVBdXnDdXPbn9tW7IN1/2puNT083KquRpmw8XBtPC7l3ubDQd6pJ+XLp6QUTa/qOPDhaRv28oONNAMDbamwsN21E31OXbZzGgPN84nS19hYAgMBGvP3QglGarZwSiZJEpmMFQRCE5EtS6YsStH1ocHAwWrVqhWXLliFr1qzYvn07Nm7cCD09PRQtWhSTJk2CsbExTp8+jTlz5gAA8ufPj8mTJyNlyoRP+RfbeBYAsLIei+2lD0nInlvCQr5mP96F5ooXFbRVBhZ8xXUuIlof9+craPvMvxbxCPL8eyycYnjyF2+zOW42CZUJ2/jZVarRM8+dYWGo/4LTe+cvGu4s/Ad/XqsqCWI3V80WqIfYvaLWAl4EG8PDAN1BaXf5nk51qKqKWLBLU0rNTkSpdLu1eAZr1lC0ILemx9fqqmGbntL6hea5eCS6qRuLxAf36fmj6/MI/KxVlI69Y9jCvfmW7j+mOVk4ZmRcS/kMnIdDz3X74K/gU3cjfWjU2XxIRTXMxITL3N2Rnlms4UM1rNhQ2jnqnPN+NWzSnjoAgD8WsnCu245dqyaUpPDKgzhfMacxl5nNdVA2A39eKj2JWRcvzuOhW2Q/W1lzXv+sTLMDWoN09l3NrjnpqD2sGc3tOOg5nYcRs4MPAHQtrnPz0ed6nXaQ68lKZxzEbIUKAIbXdCdKL2FhPfUyvfv9Tk81rEhPdhm7s43uydOMXZVypaK8di/AhvYHnRtZr/5sZFl3yMnvNqTP82u2/7znT+UzrzLPmCx5QN/j82t4ZkVJxflSNItmErvXcu6/Tsf6++8+1b8QUxDiR7YPFQQh0ScLJ5G+6KszArdu3cLYsWPh6ekJAHj+/DlWr16NPXv2IGXKlBg5ciS2bNmCJk2aYOTIkdi4cSPy5s2LlStXYv78+Rg7dmyCE/NxM4nj1kF8km/4UncAQMl5vLf4/Aosko5kIdHi7sOi392LxFL29OxeUqRPTgDApqes1Obq3EcAoGF/eo5eChYkIbqFm9aFecTf9yOF5StriGejyUd++GYWkTNvkYjU1+zI476NZgGOTuMwu0+8CPjoYRJ/vhvZPSLv1D4AAINX7C7zKYrE3Y13LKBua4ydx/NIXA+ZzyO60W1o9DbfXyzKUpiQGB/T5IQaZtSKXaKM7tHobZ2uLGTdHSwAAG6v2cBZtEi36Lg5l8+95byjTAVnGiVuqVnQu1K3biNlS94CVjlMeXAszM9e2oYPOPsjjx0A4NYBvufaG3r32zmOatj1tyRGa7dNB/fhZDScfMYzHYftqF0ZlWABf2kh1UmpaTyTcTMnG68R22jrV6UJvzvqET0zfR52uymdgQ55y+dwWQ27spvbX719FDfw77tqWOG55K7292j2y8rgQvU19zrPQqXSnCOwxJbqsZAjp7H4Knr39uf8vehejNrzq7y8krtEOjYehj8mYd81H9fxmPGUr6Ol+R7LzPQT8eEut5V+eXk9TgndgvOOuzk9hkdpPUT/KJ7p8Hmsm6UqkA56n+ge42x8z8DK3EYSi4FB3IXbgiAIgvBfklT6oq8aAjt27MCECRMwfPhwAICxsTEmTpyIVKlIqOTPnx+vX7+Gp6cnMmfOjLx5qfOvUaMGunXr9k2GgMtWEhijPFio1d5Go8TmRizUCs/kz+vY0kjtqdXsatJ9II0Ca09aXeZGWTXy4BFJ67UsRBRzEoRtOvOMQYBuC89MafhB/QqTAM2RKgpwJ3G47gmn5/BjErVW1twA/PXJr9vajEda9f9hgaofQCIo49BeatjwSpTfkLIssitakZhqtIbDTvXk5wzSjZK7+3B6O9Qkw8RQn8Vkx7z0nNqH2Yf90/YL6vVe99IAgBqruHwyZac8Xj7IbkfQjejevMYj6PpZWVh2yUf5bbzHQg1LXYL+D93Kpw1XGUlCdtNcdvNxXMWLl61M6PlN3bhMn3nReyJv8u5MXrrTnLu3N0Wnv0j0n/Lhsnp8i8o5bSY29sq1DgAApGmSUw3b1zhAvf7YhEbZ2x/ld7/T7TB0c8hZNSy/JcVrOYOf4/GGDZvimUn8+jerrYZ1zk/CfNccHiWYe53e8+YILwKfNprLdOA5cuUxNOL0LG9ExsGGp1xf09fT+0JdjqthqcvzBv2hb8nAyZWajUYDW5pp0zvsqYa9T0Xfi5breNbCNhO34zqVyIhJk62wGoZm1A6N2F7Fvp5UFn89SAUgZvtVnkWYs4SNlD5LkCgMfymHR0EQBOF3JKn0RV9N5rRp02L9nSVLFmTJQoLh3bt32Lx5M2bMmIGcOXPCx8dHPUPgyJEjePPmTXyP/CLLHpKQcczOov/gCxJylwYcVcM+hbH4nTWU/Ng7hLKLw7FXJJIKpGGBmiIlib9IKxaGZTuzoNm2gNyE9KAZldal59E/Gveb4nRdezKn2/Dac/W66mQSQcsrs+913ulUDqWG8rOr9GL3JvdrJNJH1ubPL/uTAGuek4W36ysyMgxvsdHj4W+hXt9/RmkL/JNPsyu6pR4AoHtBLtOiJUi8VVrSRA2bUopdaByH0zud+/Nsw813ZAi8O80j/khNRlhkKXZJicrF6enZlc5AiGjAAlXvBc1wGL3nEeAzA2lbUIN07KplpvHTf65zddJuvXm4JYnf+kc5X30nUToymfJI/Jrpnur1wPFkaM4/zq5V+ja0RiJkO5/X0NSAZ6T8/Skdl7sFqGGzc1E603VmYb1uHLn8mBpwGo++ZHeik3sp3wZ5uF1ERlM5W2nSe9uD0pbDkdvzGV9uxzHrBU4M5jy0PkLPfKNxF9I/Sv7+JRc4qWF9CvLs0oDGZFx0Pcxl/pc9fd7zLNf7nTWUjoIL+X1nnnIent8lA6HwHxp3qytknL205O9a6zf0noY2/JwLmu1F5w/n+xNLUhmFEQRBEJIvSaUv+m57xdfXF926dUPTpk1RvjztKDNr1iyMGzcO0dHRaNGiBYy0Q4IJoKgFjRCu1GzNmTolFWTRufZ49ZoE0yndKC4A9L1oAQDYYsui3mYxiegXW26rYUoBEoH6ANbMISHTdR+L8VchdP8AF96xKEceKp4wd82C3KMkZAwAhFeh0dQM5VhEr65KMwp5l/LiyMFOJA4X9+bR64v32UhKoVtZvsqa3U8OOVIea25l0dWiJImltA043VamLO56VSJDYukB3kmojW70/4Nmx6KDZ2lU+g/e5h5OQ1hQG1XWnbIcziO2mWNOcP6TT1Q+/4ieaZmOn/3yIQv8cFvySS+l2Q729lUqZ+12r/ad2MXm2BiaKbiuWewaotu96GJLrps/blFe3TdwHtq5s/D8+ynVU5Fu7Be/hVzy8W7hSjVswbE2AIAKA3k//WypOA+PP1CZu3hyevZPodH08Lrs3pVC5+4yrBgL60IDuN0oFiR6D7Xm9SQxTJ/4luOVI+HdvyjX62AXfncK3aJvazPOl10+Kosts3m7ztRD6TvZNAd/L05r3OdgR/XYoAgL8OGnyThooTEAa+6j71/mHEboaUPPuvWOjZ0DXnR/6Ho+tdg8FaUtw7DSatiHv6jwXQCk7EmzB6ebcx7XPP5xQycGSWQURhAEQUi+JJW+6LuS+ezZM3Tv3h3t2rVDly5dAABRUVGwtrbGzp07AQD37t1DtmzZ/t9j4lDBkkRFtlQ8Quo8h8KMrrKrxL5KLMBKpScR9CKERauxboeSfSd4ZLe3bstMfX1gwnUKu9yJBVipeSQyD/fmUVXHDiTWC/ZjX+dmOUkMzThtipjxzJ12PENRbgf9nyEji98tD0igDlnO6XbXjIae7Ue79IT5c3pbuZE4zp9Dc/ZASRLP78M43QPc2G1kSW0SmUv12QptuIsMiZFVeWZhrxel5/pDfvbN5SxgSw6gfOuX5LD9A2n9wWqX7GpYdWtqPk45WDiW9ON1EK3KUN3VyMSC79U4CwDAHxdYtDfJQZ93H/oBsCaXs9m6g7wAoOViKstCXbkNZGhAgnntQl7EWqId5edVgB4yZ6VZhCFFWHjHLA4/+ID35a84gN49cjCX4/jKfM5AinZkNHWqz2Wq70ttwGTLPTXs4UVbAED+5WzgHZzKhrDDCDK09nhymS7XHVKmz0WqHiQW1IDT06MGfx9eV6A25BXMAv+klwUAQCnHD8qoO6dhdj9enIwIfk6+kWQsZk3JzwncSTNbp9rl5ueYk+i/ffkTJj6gZ+YtzfV9UOfOVXhuMzWsme5wushoNqgq7SKj+X6AIQAqi7vvOT1ewdxuEov2sD5BEARB+Bkklb7omw2B4OBgdO3aFYMGDULjxry7h56eHrp06YKdO3fC0tISa9asgb39t+0H3uEwidaa+VjU56xHwmn+eC7RnKlZwE69QWLLaYdmB6AwElPZU/EIcmQECZoUmt1olj5gMVq9Mj2npzvf020qCZ5BRVn4FK3HO9fMWEnipsEuHrUPO0BiKkNbFv0xaww2Pdb49jfkxaD5a+kOh9LURs0sJNzXr2Ahm+csCSztllTFyvNNHUbS50uXZlTDJl0h8TZuLYsu23pUfoNrsCvSgEuc77rtKL/bRrC7zJ1zdJhXoRE801G5IRkzE9gNHXtacnr7nrEAANwP0LiajKXFshGa7SartKMZCL1AdnnSbr97ZxyJxGJjuPwqZyMj400ndkvy/UR1myYVEKCzPXpodhpK0ZcW4jod4RmIqzpDonwTXp8QI/4BQC+URvp33OBZqshSlN5jmi1gz/tSvevpsYCfepOvB/SnPNik5ba92oLagJ5m3QrC6X3pUvD7rr1lkbyoIs049eMddhEUTO0ruwOXhd8bquMwOxb1Jqm53fj40eenjdkgfbC7GACgUGs2cAxa0ej+k9FcZhW28exRts7UzjNq3JtmH6P05szLhlDMwnIAyFSf0mmu2VCsYx42wBOLgeH3T8ceOHAAS5cuRUREBDp16oS2bdvG+vzBgwcYO3YsgoODUaZMGUyaNAmGScURVBAEQfjPSCp9UYK2DwWAmjVrYsOGDXB1dcWcOXOQJ0+eWJ8NGDAA7u7umDt3LsLDw1GxYkWMGTPmm9yDwqOvqddTbtAo+9ZZ7E5TpjeJxwUVAtSwSn10o45RnI0Roy3U61kzKG60BQueGs1IuPfUbJM4/ArdM1hzUNPg8Ro3jgp09sCs+iyCQiKpkqefZhE9SLf7yZwh7Bbi+4BP8O24hfZLP/uMKyzmZNm7ml1fwv6htGUsymLSTLOPft/CpHQPv+R37+qwBgBQbF53NezZmH0AgJS2vDVnt578zH2603Z9b/Ko/fVxJFYbH2PxVygd+3a7TSfR+/hQeTUsXxcS+EunsoHTpycJ+8F/sL/7H7vVS+i9IWPHwIdFYJRur3/De2xwRKejNC6ZZaGGjT3H73l3gWZI9AtzeqOeU92ZFWQDcZcThR3XnIJ7/BUbF3d1Oz6ZpeO6SWNBFsnyGgFqmNtrMgD09bi+Fk3i9DoOoQp1WcJhRTtQGRhptgXto9vfX7uW4KIPp61JbiofL812sKd0B9WF7P9HDas9QLM+ZgflceEQfk7fhvS9MipTQA0bOIS+A/NOsTFTuhC3rzllaQ1GzCFjAHB4vs5Y0sws9JhEeY3UbJtaKzO7GzWrTe92O8snIdeZTflxH8Ftao7mPYsr1kBiqLTnXKy/LzSpkqD7fH190bp1a+zZswfGxsZo1aoV5s2bp26AAAAODg6YOnUqSpQogdGjR6No0aJo06ZNotIr/BiePXuGY8eOwcfHB/r6+rC0tETVqlVhY2Pz9Zs/Q7YPFQQhsduHJpW+KMGGwH9Bno7bAQCZm7IPvPcmWpwanZ4Fr5KSjYvS9iRobqxnt5Hzyyju9r9ZYEUrJHKa52J3hWtvWPCt0R28NaUUb7P55hOJwE67eOjSSLdby5NevLvQ0CtsrFTISCKodhYe+W15igTqCBt+du9uPApceRQZVW4erKbuONNofddzLFTffCQBtboqu8O0d+X1CVV1h4/FpAEAMpvRM1c+5jw8/UDlt6QSuzRd8ecynbSV/tfXbF0aXYxmGR73YcGW908Snbalefj+6lMWk8d0C3pPa8StUw56T+FFHG9QXRKE+dOwMMxowmUx4QbV8eN1fKJy2kY0G/PmFhtrZ8fSPbXqsRHWcgF/cT7qzjhIoVnQu4m8stClLocV0qRjzjXKbxlNfR4+Sm2ohQOL6O2uJI49R7N7zp13fFZEM3sS7mEOvA6kXX1Kj7EmPV7B1CaP9OLtOs2c66nXqXUHpLk147ob7UGG3XmNcRl6ir4PuVvyd6l+FjZiY945swULHqPGZNhZlmDj6eNH3QL0f/h7Y3yMz9oId6DyXd6W29z4i5SeTGk5X6G6sq9uxS5ql99w+aU24vreYpu4vZar7o/943vIthgCA+OuzTA3N4e5OefVxcUFV69exfTp0wEAS5YsgaIocHZ2BgC8evUKHTt2hKsruY55eHhg4cKF2LBhQ5xnC/8tmzdvxo4dO1CvXj1kzEi/Vf7+/jh+/DgaNWqkurAmFDEEBEFIrCGQVPqiX2pOe+FUKogJ51lAmDqQsPp4gHerqdaGtzw8tYcEkb7GL76ybpYgOj2H7RutG72/xUK2oiWLlzu7afS24U0LNSxmd55q3TRuITq90sb9LVrrfKFLpmch/PgDFenfQTyKm8+c3jPrDrsQwZHTsaACCbRsnXaoYcWNOwIADM6zj7dJXcq38yUW/5PLc6Na9oie6ZCNRZup7pCxMuk5r2cG08JNx3RsKEUW4cWy1pXIcKnRgJvHTg8qv1UPeX2CgW43m7ElOFv+BbnMF9+ncts7kA8PC9DteW+r8TP/U3cmWMvaHHbkIRsmoSFU6Pk7sTuRSy1K25mqmnpfrfsitTBH3VKU7zPe/Jw3/iTW/WftU8NidtXxCmbxv+6CZhbLKwAAcNCbZ1FM3KgtpmjMRoZxekp73o431bDGfdhFK2bGakwzFrxt8tB79PX4fUXLks9PwdnsVlc6PbtwxRzc5RXMbe7ECmqn1buxa5BZPnr3pJJcX+XWWnB6rpAh2ntjVTXoaRClY3FFbivlNlI5G6RjY05pW0i9rqibZBh8nPMQc7K3qSl/B7xu0HflCYBzgyk/C1odUj9vvpa3J00sn+/UsH79eixevDhOPGdnZ/Tr10/928/PTxWRAGBpaYnbt29/8fOMGTPC15cHAYSfx4YNG7B3716YmprGCu/cuTOcnJy+2RAQBEFILEmlL/qlDIFxZ0nIvp/NDtBZJ1UCAOxZZaGGdXLjZDdoQeLvzScWHZf3k3GwfQSLJaeB5IZh15tF/aRhXHB6uv3S3Xqwu9DQKzSaurACj77W2EkivGqeSJx4TULaUOMi0rcQifqTr7WLH0lknpjM24xGNmTXqhKjSHilb87beaq+ZdU1h4PpNOTT5ywmIwtrzisIpTKIMUYAYFZXeqe5M+8kZDmGfMGb5+UR4vl7OLUjStNMwIgTGgPIm+Iuv85hlrozDo694ud0zsfv7uxEBkCKXvzuuZt1swzRPML+Z0+qpyFz2EVIT7O9aPfhZKRsvcOGS0A4id+hbmwU6YXRM5VNF3B8NYVlGMGjy5ZWVD5HPGzVMMf9VHeR0Sxkb3bnmZCSfWgE28if83jnNO2GU7gb16f+HWpL2SezC0w6Yx79NupD7gnTN3H7qjCY8jvoMufBtD9tSRrF3jfYeZL/yFuSviOVrTTnUOhmbmzSsmvUwg0ktkumY+OqcF5uK4XL0IzWSlcOm9GE0nuYJ15gYUHt2MhY0878OD3WptS2t3bhmYd772kmpONRNnwzF+GZrRbH6Nq8DG+/6hX8bTuM/T8+P9W9Y8eOcHJyihNPOwIDAPFNjurp6SX4c+HnYWhoiMjIyDjhnz59+ubd6wRBEH4ESaUv+qUMgcJZSOCaLymrhg0pSoJnyQMWoH6LHqjXh/OR+GnezUINuxpIwtr/E4txvfckcg65sBBL35IX9BrrhI5dPd5TM6ICped6Ie5ITE0p3kVPLjqtSLLWLZpcvoVHcef1ptawczNvmek0i8XmpuH0edtl/MyUqeiZARqXjJvDdPFOc3ruved7Cui2X9VMjqDSdBq9zZaS07NpA5VBQHYu0xSZuKwa5yDhfaIIG0qHw2ikLfgQq8R6g2jR7P5/+Dm33rHAH7GWytcuW4AaZruZxGH0IU81bMg8+hL068WzJG7ePEPRqxCV1XXNKcpuOkMrnWbr0u0NSaw7bOPnRGl81z3dqS1tyswGxYeTNDIeXVNzAu84FhQGfvTMx/vKqGEVdtFzqnfh+iyXwQIAUMiC3b/ab+XRSeNLVG6NBrE//yU/aqe5UnOZPRhGvkr5/6yrhrmPYpGdZzCJ7Eu5OQ8xJ+dpzzA4O4Gumx3luvH+m0f6tw+i8tuxi9P7113KQ3AwP2eDXQAAdpMDgIEnNSdOP6O2ONuM1ywsOUL5NrzLLlrXV5Oxs/whP2eJZgvZGWUC8KMwMYiO9ffn065fwsrKCh4eHurffn5+sLS0jPW59mwUf3//WJ8LP49evXrB0dERFStWjOUadOnSJQwaNOgnp04QhN+RpNIXJdgQCA4ORqtWrbBs2TI8e/YM8+bNUz/z9fVF8eLFsXz5cri6umLRokVQFAVZs2bFjBkzkCZNmv/zZKaoBQmV1QN4pLX8Stq1pHi6CKzRub7s3Z1J/byDbtRx2wkWzBY1SNTlM2eRo2SgUUh9/1BE5iFRkj4tK+ZUOhea3DP5hNRJJcntZsw1FpZDS/Go9eMPJMxXnGMR/TozFWnKQizU7r0nET6sGbvItFpWVL1uP4Xeo1+Y3xN4ldYBWFXhtQgl65IBpGgOarpVkD9/OoEawrjr3ECccpCQnXqZxdu9uSSoe53nRppRs91p7pLkq2OUiRuWYWq6J2vHnGrYwbsxI8NR6km3JgZsAodFUVid7Vz/Ls0or74NWOj36EPpXTI2ENWGkCvYgyXcBsrOonaxaQvXu7M7PTNg6X01rPFEimegb4ToLJTf2TU0i6BtKA9LO1zlfPWixTvRmu9r6qKc3oL16UsbpbBYf+tCot49Ndf788bU5sI+sYie2Zjbyvoi1I4nluL1HaWm0/01eZMiPLlZh+I/5tmENu5cn8uHkvDud4SNjEyDqM2+CuV7Gu+30F0p6vkLBUYGqJ/XPUSfrx7A9b7Xi/IYqfFoavQn16dZTjIqOpXh71ohCzKaLDVrOpbqDmEr3IENmHHX2Lg69YS+I+ZcnXgWyEZKMZ7Y+C6M9b8eJz4qVaqERYsW4d27dzA1NcXx48cxZcoU9fMsWbIgRYoUuHbtGkqXLo29e/eiWrVqiUus8ENo2LAhypUrh4sXL8LPzw+KoqBMmTLo168frKysvv4AQRCEH0xS6YsStFj41q1bGDt2LJ4/f46jR48ia1Z2V/H390fr1q2xatUqZMiQAfXr18fu3bthZWWFBQsWICgoCGPHjk1QYi77kc/wgLMsxGL2MX/kycl8P8dFvX50uyYAoOQizem1H0l0KKZs5yjGJGhu9GDj4H4AixxnVxJ89QuwIImKJiG7bwwvjjTpQE7R+poKti/I92zbQWLM8DZvhRn8grbhdD3HO/es1mwletWXBGHJjCw2r/mQ4DvqwCP5KQ1JbO74m0flz/nxKLnHa7pnVc0ANSxmx5kJ59nI2N+IPm9zihWXVggv0C0iHqRZi9BLdyrtknv8nFxpyBCYUJLXKdTXHIAW8ZqMkLBdZ9WwQVttAQD1snK+hl6h98QcGAcA5mm4gN+9o8Rl0KzFcNDtqHPRnw0un/e6BeEFWRCvmMiLsi3b0QzF8YYsSp8FkVi3NuUC6HOB8502BaWpa37NgXVpqa3Z7ub2UycvtYHtK9hlx7w6C5DwMGq/WxpzWemaJOzn8HP2Dab3NenHBkxUXk5P+oL0bm35FE9HZRmzHgTgdSIde7PhoaRiwyXoyhUAQLYJjmpYo4L0nMqatTMxZy90zsdGzagePNKfvhd9H157cdutW47qYWhRvqfTSQsAgGNerpvHgTyzNa88h1sY2yExtDp1Jtbf22ok/AfywIEDWL58OSIiItCsWTN0794d3bt3R//+/WFjY4OHDx9i7NixCAkJQeHChTFjxgwYG/+4MxCEXwNZLCwIQmIXCyeVvihBhsCYMWPg5OSE4cOHY8OGDbEMgWHDhqFAgQLo1q0b3r9/j2vXrqF2bRriPHr0KA4cOIAlS5YkKDF5G64DwKewAkDlbjRsaKJxe3DdpvGPfkmCybQJu/l82kAnrEblZFFqrpslKJiZn1Mzk0Yw3iRhvsWODYXb78iQuOLPhbv9JAvGGrqzB+68YlH24QM9v4jGH3tppQAAQKVZLHw29mbRO+6aBQDg1Rwe3VZ0o83LNGcCdHegLTrLzqughl09ysIyXQnK7/s/LuNzIqLYx73hMlogenyu9uRbNigiC9EsQ4NKnIdD7iSesxbikeiOhUgcz9Zsn2qRlstieU0qy1Uao+foGhrdNnjEAjW8Hi0gfjzKQg1rf4brxk+39qFMBjYejtynutnpxPmvXv6keh3yiQyx938PUMO6nqNnpjPmOrzgRc/JmI7z+siFjTiDJ5RO47b51bC2JSkd/4SwofkkkOrr+RHeMrSXZpF5+hT0ziXXuCzcmlHbLbuWjavLnajMRl7lGZyO+dgIabOa3lOiHH9H0ury8zaMyz7GPexNEOerisb42rWM8qXnrVmXofspKD+S16+cO6FbyF6O0+O9lg3jPL2o7voUZMNlwAaqr5RZOY3hW3gHpXdetwAA3TbzOSS7J7Br0dPDnZEYOpw+HevvDdUTtwuR8PshhoAgCIk1BJJKX/RN24fGnCUQYwh4enqiY8eOOHHiRBxL5NOnT2jTpg3at28f7+KI+Oh/8ZR6bWlCQnnVXh69TZmTRFSMnz4AnG3Go6kdz1LcG1Me8T1dCwKIbQBc3suGRKlGNCpeJzMLz6XXSNjudwxQw7Y+I1FTU7NHeqcDLI4ciuoOnnLh54zsQMJ/YlPO173rNCvg/ZFF20LNKHuRtPT8ZZdYREUcJZEUlZnf16kTicxDTzle7gwscC9eoudMbsYGxyrdOotddViEL75PZXrOl8V8O83hTn9dp8/fvOQRX30zKvMPf+5Uw148aAEAmH6T463vzFtnWY6imZv37zmNmTPTc9ZpZjBqVr2uXmefRPes0uzhHzPDMdSVyyx8ORlIUzezMbhIsy99Kl0RfYrkdrPFlsogTLMoN4MJlW/JBnyQmpJaYyAVJXemdAVY4G+2J+HuuIv9/mLaZ/A+FreV+mp2uupHPw7HzvDC4vrr6d0DanL7uvGOvlOXhtxUw0yc+Z4YQi/wWo50NWkWYkAZNvwm9af9/3dvYqOyt7uFen2wAZXF00D+LjWvTWLdsBTvjBSdkY0YO0cqg41tebuy9G2pDei/5++AYQndepPWbGCPuMoG+jN/+h58WHhXDXt8rlecPH4L3c65x/p7VRXbRD1P+P0QQ0AQhMQaAkmlL0qUITBr1ixYWFigZ8+eseIFBQWhT58+yJYtm7oPakIY5UEjugfuahauFiVhtPcOj6Yfa8GiYrcnCbWY/dcB4Ipu3/oddVjwn9O52gxoyG4qc/fz1okTupG7jdKSD12qW0yjEnXs6+EOADDLzPvFVx/PI6gNs5EIWvWYhWhQOImdEpptIGeV5c+LNiARNHoh+1SXykCCulld9pVXrEksxvi/A0CqKuzHn0O33rVHARbyM69R3D+rcJm12kVhw2zZ13vLUxa3/1zWrVnw45HoPTNITVubsZBPbUSCrtI2Nmrm1+SR4YqWFgCAAkvYOHAsR/cfvcuiM1tWug7SLFItlokNwKue9HnIdhbotUeSz71jDs5Dj51kzHS15XtXd7qkXuebSQdVDdMcGnfRj9rFpgW8zWbeNlwPf5YPAAA4DNGI24pxfY4jbtBMx/nZ3E4rTuM8bh9AecucksvvZQiV25w7bERcu0DvyV5CUx9XOb1PJtIMWb7xfG4GrEmgj6zF7euQ7qA5L82hxdoD6d4upvUmG7bz4uX2XWk2Y8daNhja7qO24jV5uRrm+ailej3ag9LutpHLb8c0aivNlnJZZC1GaXzlxvF2j+PvbLPJ3Eb+XuiIxNDnwqlYf/9VKXEHlAm/H2IICIKQWEMgqfRFido16OTJk1i9enWsMD8/P3Tt2hUVKlTA6NGjv+l5OVKS8J5Rk4Xs4CZPAQARDdk1o9E+C/V6QU0SSZf9eeT2qD0ZD/fes0Cdco6EVYYR9eHanAyEwy9YGLWbR6PJm3mhNg6fJHHyaStXZuVFvL/77Zm0+Nf1FI/ins9M7wn1Y1G2uC09JyCc09P3Io/YhnnTiG3tLCzAsqakkVijPiwS1zUkkd1yJhso2rUKttYkipc9ZEPh9aUAAEBpx9xqWOmCJFpnreN0T+7OInz4SBrJzzKuvhoWHk3lXHs7+6uPqEJ5CF3uqYZ1vc0i2uAJ1d3IabwjTwbdotK9V3kG4tnFuAdsvE2rMaTOk0B9sJe3IY1xHRp+iuPtbc/PadGT6rjQH7Zq2IzSAQCALse4TKvkJqNh3Sx+zoF/uFxiduJJact5CHxI9aCv2VL01Dxqf66abWONrrHr1eSb1H7vnwxQww6Pomd7sicSjvSjd7fTLAa2KMBpq76Xvhs16/Hn00pTvufeYeNhdHEKa3NU01ZKcd1ZD6LdpNpO5YXISiEave/pxiP2e5pSeo+W76SGVezNBnYmR5pRK9mCDdKWOylfem84XvUsOqOofSpsXU1G6bjrvNA9i2bBdGIx1k/w2IYgCIIg/Csklb7ouw2Bd+/e4dOnT8iWjQ95ioqKQq9evWBnZ4c+ffp88zO9QkgszNjPI6l6jWmEPmwb+1rlWsgCdeg5Ei0+ml1WxusOMgqMYGE0uRoJqJehBtjxnEYs/5zJQiVrC5rluNWZjYNa+2kUc647HwvdoDKdfrz6RANgJY2mltb4rp98TRU/aS2PSg84SELOYBfvGrRpG4/ElttO26VOu8ki8sgpOkhsRBNuSLozqXBkHKv/Jnv485iTeR994Hf7lbYAAAy8xO4jz3yo2ivbs8EA8Mi63TLauebkaQ6bY0Vxw9bwOoY1lrTzUUTNHGpY+0bcpB4F5gQA5EjNMwv9ZlNZvd23WQ3ruo0O+6mXld9XKzOPJj8qReUy/joL/R01qN0FR7xWw4p3IYHeZ3h69J5Io/ZF0vIMRYtuNBqtF8AC/VBpEvh2A/l9LXJzWxp02QIA0Lkkp23JXp1r1Ucexa62lASx3uYrapjtQl4cHhRB9aRoNhZuspvap11Rfs5HnfvSnzU4r31PsOHi/9dDAMCoNWxwVelKeYwqyO3H5RHdn7cDz1w9deP2HmBC6TC6ye0iKj/loYAVt4t2R+j7VTknt6mo7Jwe3wU0s9B1Gb/n2gP6filZ+TnvwylfV/4xRLrqZPDeGHxM/Tw6WrMHfKOEHcP+Jb53pwZBEARB+FEklb7ouw2Bly9fwtraOlaYm5sb7t+/j6ioKBw7Rp180aJFMW3atAQ9c8cSEmodnHk3m1ehJG6s7GqqYRFRLJw8btD/Zcqzr/zus/R52VJcC4M2kvDZ24dHex/15lFM71AaqV6lMSh8femZ7XazoBmwwxEA8CSQBfhIVzY4WpWi55esxf7UtzeTG8fWHSz+3TQjx8tWkJESbcFuI+PbU9qvveV4trr1CZEaI7NSfr4nhW70+qY3V6vvKxJY+++xsdLZkUaJ1xxno8exBT/01AFKj1kBFnw3JtO6i5yjedvTg3VIPP+VncVtVWt+j4duG8nJmq1LU5cjo8isVA81LDCC4vXXbG+5ZT7nK8bta2nLrWrY9tZ0+NrtiRoBP4AEZoRmCyTvUG4Dr29Qm5x1pKMaFiO8BzXnxayOCwuq17c3kqFxS7NVaFRJMjKMM/Is1EmdD3yxxXwOxelDXFYNdD71LRrxPdtPU92MKMYzYHkK7QYAOKztqoaF7udTtY3b0MyC8w4WzlZNSISHBHO+i1QjQ+HBCw5zaspt8kDfewAA33e31LAL+xwBAPc1Pv6VdNvKzh/AO1X1mcuiv1QPes9HzYENN3WH8pWz5TUSJtUo3Zvqs4taxbHsJjRsV8LWESUEoyQyCiMIgiAkX5JKX/RNawT+bbLPIxecIfVY6C8e+lK9TtMxHwAgIICTHP6RBIjRdXaG1vchIeL/nPeLzzq2rXpdJZ9uUbE3i8i368mNBSYsopf9SQZJ29rsGmRmz+sKMlehz/0W8gFnlSeR4LnmyQI00JfyY5iKn12xMOfBTCfgm+ViV5OQCBKo/RryCHPxubUAAI9WsTC8s4UXyBaaTCIrWxkW3hnM6Nnh0Sz6752ieDmrWHBeK/No8R7duotN11m03uxEItLJlUfGH2tOOM6Zg4yBYTYs9LpvIUPK6CKPwL+7Qzsaed53VMM6n+H3xPjI7+jFbeCdbjecXis5D7nKUx5d7TivBVqyCFdSUt1mdmLj63RDco3Zptl+ddx4yve0yew2kyUlu9Mc+IdccApZcHocspOxU26MGgQlF42c96nGhuaSY2wglS1NdX9jI7fTmPMsoDmGPGZx93lfLpNHAdxO/zlJrjzje7Phu8eL6ma+bj0DAPS+wMZ053w0YzB2Bs+OpNa5OvXVLCqOVigdjjm5jivM4HfnLE+GYZoUXO+hkVQ3fm80YRto5qvocHbn65CXjZ0Bupm2VKk43yOqsvHRMV89JIZJN1xj/T2h5A/0OxJ+C2SNgCAIiV0jkFT6ol/qZOE8OteGDnnZleSabivDC396IWA7LZytNJBdUdrkIQHhfIYFmPKeRMdaV96ecN8/JFTss7LgOLGYF1yaNqX3pErN4mSibr3AnANceeE6jTjrjCn8deLHqD0vMH4bRvf3KMPvOfqShM80nY86AARF8Hs69yMx+qp7TjUsRyoSniaFeNeWlVUoXrU/Oa8RCgs5wzvkS+82kU9qylqEXHBOXeRtqxpPJWH+RjPi77CNrzPoRoFn1dYs/N1O6T3djAVxyTlUHzcO5QFAZeFwnP3Ld3em/La8zWKy6lJaaHrqNQvD1Eb0+YdwfZSsSMK7+XpumjXKkaC+PpqNDIdDZODUPsJpvLKRjIKuZ1nUe/mxwRUQTttejhvH7x42jvzUJ5xiYd24GI+2b7tI777cndtkuRH0TKOi/J6WupmgbgW43vsX0ZwkfZKeWawt1821+1RmKQ4+VcNaDCPf/VPeXM426bm+/W3onYs8uP3E7MRkpvnNCgqhNK7W7MhkeIsXI6TVGUizpvAOUtHWNGtxswkbV/sHUr6zmEUDoBF8pxPs23/NeRkA4PJNXkB8tRy52e3nCQEMcqSZhwKzqqCQ7uvSUWMcBIT9uDnUFElkFEYQBEFIviSVvuiXMgT8fElldzvHYnJyKRJ/DTVbFz5+wyOt8z+RaHEYwSOoL0JolFxfj4XGM93hYQWKssiLmTkAgJAH9B57jftEKZ0AuxfAxZRSd2hTl3JhWDmLRmfDbHiRb3gWEpRLNdt/2hfRbQn6kF2IvEJYHPedQAZQCn0W9Zse6rZKdWA3jD9ukziMysejr3X28XsOrqVR4N4XAtSwFL0dAAB337FAtZtFI7V7r/BzjE/w7kSZBpJRNPwEp/d0WzJCSrRl4d10Wk4AwGgPbuyPhh9WrxX3SgAA7zMH1LBWA2g9QP+dXF+b2lE9dXJhAWrwjPNgUpHE78Tr/LnPMfJtz96I3dPKdospv1Do6Sy2iDIsvPMUOQIASN2fReucCTTjpP+CffJHurP/vctoEs8v2vBzojNSmRtotOu2YVR+9bfyDMT8eyzg99Wm+hzrwe+pVpPS6OxcWg3reZ7y3TQn19fO5xqXnmbUTitXuKCGZRhOC9ijNb85syvrvjejOQ09VvEI/ZorOotWc0/MrMbhy9wuzAzp3ftv8HdAfwPPvFilLwkAGHbVQg0715M2EGi8rhPndUHMeokonNa928OC3a3ym2vWCCQS7cFqgiAIgvAzSCp90S9lCHxypZHqaUtY8K1/SiPE5VrziPXlQ+zGYlXfAkBsIbFvO4lVB437xKtjJOh6R/Iobas5/PnWSfRuzxB+z70AEir3LrNAL1OZ7rm+8w2QhsRsigM8ovsoNY3oak/q3TuNXFEydORtRk80Yl/6VyF03fMcjzDr69yF9jTmUXC77nRdox8L1fBodmNpoNvi8sSf3PimlqbriuN4BLl3BzKKDO/xs3esY2NmyBVSuB9fs6FUqVUAAKDMgJxq2F3drkyzygaoYfudeKFnuK4Qcozn7WVfhepO2G3PRlrL2jT1YtC6khqmZ8ni945ui09ztksQnZnWGliacf4XLKCw9ofYkCyTkz8/9ZJcTqqX4OccX0GLb5ce4neX6c/1PXIxLUoefIFfbp6d8nC9neb8h2ga5k6fQrugmUfOG7vSyPvKKpzvSgNIpC8y4XK2bW5BeX7HX82CaVjMX3tDZTF4G6+ZCY+i9vNMcw7AyseU3kYdeXehVdN4Biz4Lm1Zu8WVXd166NYBFOnJM279Cwfgf+2dZ0CURxPH/3QpKkEBu9h7RxELigoWsGEvKHaNqCG+ihoN1liisfcYeyxYo8HeKRaMvcWGDRQboqJwwL0f9rg5FCnePU84md8Xz71nd/bZXW5ndmdnASC/Gf2tzJtH5ykqzBZnNerbkuGy/IpIq1mLbgCvMb8TAODeuofqH522Pamf/EPp725wBWiFmZ4c0GIYhmG+XfRlLsrUGYFFixZh3z6xmtqoUSOMHj0aAKBQKNC/f398//33cHJyUj+7fft25MkjJvbOnTujR48eaRf8CWXrLAEAfOxJYSKNVLqN0Qk6K1DI24E+WwlF78YTjWg/ZcTK+b6rpEwF94gBADiOp+daepEiN7qKUNBSIgoB5L7jW5EUwzlXRJ6pjqS4lK91XP151xFx0NSrL7lcFB8kDIB798hYSX5Nyp2rizA4gheS77qijlhZzmNPOwemqo/bPWPUaRYm1H3WpsJAmHWJDKUUi/TKa1p9Xe0iVtHLraSIMclBEerP+XqIUKNBnvQOXY8LpfbNW43zGQni8zhnUmSbFab3qttYGFdb9lJkqYeqC8EKmGvcR2Aqymm5iHYJTMJJabVR1WdINZJT21b0sc8BUiajI0X72thTv8ceI5/8vkOFofVHv8vqtOTm5VTy6LnSo8jV6/krUbdXr6i+xYqL8jXvhRhZRdStwVIyGFJcmgC6ffrVWWpTn17i2VtvNM6qxIs8jexJsf59KRkXTbxFPxy9TON4aEPR5rO7HlenWZYQ52mSI0ne4DVV1J+XqA4bu7iRweVXWRjQHYfRrs/eJcIo17xsbOQBesf/qXz7i1lR+4Q8M0n1LgBwaIw4N+Axq4w67e/RZFCMX+Wg/qztGYHV/x5I9f8+ZbUrj8l58BkBhmG0PSOgL3NRhjsCoaGhCA4Oxs6dO2FgYID+/fvj0KFDKFWqFMaNG4fr16+nev7q1av47bffUKNGjazXZoCIsmK6/II6Kc+P4ibV1yVI4Xv2jFZ5X70UClGCghTU/uWE4r73B1KsOxeqCgAo2RTY2Fj4Ortvo9ffe1oo+B3rUzkbfYTxs9GlrjqtUkeh5HQ48gGXrop6GLah6DA/nRdKUruxpGDtuiCe0zS5vitBBkdhC5V/+Xi6qGrp/s93BJotE6u7fU7RQdAXGoc0axQXxsxbBSnUlzYLBfechpJdfK4o+/wQUjDrJjqoPz8/KPKU+4luBj59ThxUnniBDKDZdUTd/rhFq87bHlirP98KEwp1bge6VG5bcFdR3nNSfuccVtUtN3Cgt1BCC1rQDkXtNkKJXDecFPRpR0WbXh9I7VxutIjw8yYSgCqKTbID1ae0atdI2YSUUaOHog2Mu1LazYNkSCWpdh40jYuuJYXSP3scGQ8DVW5Z53xpxb+uLxkK1boK4+ulxmH0lB2nNxr3SxS1FHU8+ITeK7kIDRz3QikHeWn8LPEREYBsx1BYXRsbUeYxj/zqtJ/P099DQC/xvbUpGbnt5wvFPV9rugV54XUyXnObiDZNCqX3vlhJ9FOfstbqtL2PYgAAd99SHyep7ij4a/VrGN0Sf3+hB8ndql5LOlDQO/UdLFkmJXoWwzAMw/xX6MtclKEhYGtrizFjxsDUVCgtpUqVQmRkJC5cuID+/ftj7dq1qZ6/evUqVq5ciUePHqF27drw9/eHmZlZWkV/RsGCQhEZtIUUPteCMQCAx26kLN2NJeXl9HNRr4oaUV1S3Cfy+tEK6OMnQnFc1+YtHrwVcsprKFgedYUyPmkmKce5+rUEABiGUax621yinOCR19WqWP4xVdXf/1xdKMcpt/cCAEJFfvPG5D8+oja9w8Tdor7TvcjAcagkFEHf0xptZyTqaG1Kyv/9WPq8qqFQ0v3PkSJ7JVbk6XiUZH9cvgMAcL1rU3pX0iuxZJKQ3XsxWa/uPwoFN39zcl9KWZN2yE31/n0JHUjtYSDa12kphQodMkecq7j2KymohS2E8j/A7S/UWyjSigZ0U3/feapwVbn9luRUqiY+//uGdg6KuIi6Rf1xT53m1IbqW9BCvIPmRWDHVwhF32MHrbDbNiJDq0VR8ewfP5OiOuOeUGAN85EBNPWi6O/LGtGiDJKobhdOCtmnxlN//XBayAwftlWdVmFdOwDA/ha0mr7cQf0R7qox++g9jXffg+JAebvZNHbfHxSr7ZWja6rTTnaj906JIhX+gn4C2rQUg2DvatopOuEsXOmcyySrV/iVFpTnwDLR364ahp1bMdE3+1Y8V6el3IZtVy030EwYvE7/o+/LjdXSH0gDfYndzDAMw3y76MtclKEhUKYMrZRGREQgKCgImzdvhoODAwCkMgTev3+PChUqwN/fH4ULF8aYMWOwZMkS+Pn5Zaoyde3FamfAYAo3GTpZuIXsW0BKlXFTWrEc6CRWXUvnISXxwkuhlLzWcOeY0FS4MOx/Qop1BQ3f626lhMuF4Riqz/jtKl/wzXQgtVZzlTuDlQl+XiEO8k4efFP9fWARUV8LS1Is83UVrjGdS5BrS6xG1KCK1YQx89s5UqZK2ov3efmRFMLKVcVzj16QAVOjPI20qRfFSmsBc/p+WIBYsV1/hdoib9GKAIABe8k1yr0ytd/CGyJ97VBa3W7hJIyHQq2HqtP8z4ldmjoaF6olFaOdm7P/uwgAUFYjI2RBgCi7Sj9y9UpSXTx1MMxDnWZnHqP+nOKite42tdnxB6It9u6j9nFwEt8XGVAK71VRc8Lnk1Fgt0Yo+Ib1aCV6wnnxXOWi1D4/ViaFet41Ud9Kw+lm5n8fiDyzelOb/fNSKOZ3LMmieleUjMHe7UTfNpxF73DzZ/Hn13ZhZ3VaNRsxRkpV26dOM2tYTf15V2uhRKdECgKAdsXF343he1q9NxsqDIBihWl8HHpC7mHbVCFHz52nPMaXVQewu5IrV8k84r1O3aRyCjSlczaWFuJ9fq4eo07b/UAYSLV70d/Nk7eUP9x3MQCgzhJfdVrUc41DNVqiL6swDMMwzLeLvsxFmT4sfPv2bQwaNAj+/v5qI+BTLC0tsXLlSvX/+/bti3HjxmXaEAh/keuztFN3RRWtPIqimMpzJlYj1GBotMjTrRTFPi9kIZSKtRpKWcQ7Uhj33RPpRb4j5aPMb0L5M9BYYS/mKIwGx0ZX1WkJXhR5ZeUNlVFhTPVJidwSd4wMFwsPoQjveUzuHtNqksuPfS6hcPtfJkXt5QWxejukBxkuW6+LelcvQgroj5VJWe97xBoAEPmYvr8yRBhA89aSPJMYVVutuILGc8V5jP2zyG1k4CShKG+6Ryveq46JS7iWXSdFNni+yBMMoGBvB5FoSL7tUc/FIeDhQ3zUaT/8LRRigze0Gty4n1AYF98ATm4UOwbGl2lnIamEeC+YU9kGqlV9h0EUXvXdW+q7JU1Ff86zo4OvLRcKg8WhJo2F0FuirTa0I7/48nnpvW9Gib7Nm5f6uHxxIWfWRY0oRnPFXRIpITgBQFmVFOY1R0R+00I0BtyDRDlPdtFY2dVNtIXjvGaIei3a+tU6OoyeEC/KbFaadgSsVWcs3LuQEXZQtap/C3RnwLit9I5dBot+uKRx0D3fCDEWNA3WuUPpzorkzmKnzj4P/bj94hgDAGi+ltqiUBHRvoEtaGfqssbh5+TgXgCAQ0/IELcswIYAwzAM8+2gL3NRpgyB8+fPY/jw4Rg3bhw8PDy++FxkZCRCQ0PRsWNHAIBSqYSxceYDExmqdMwDO0iBmn1FrFg+iaNyLgxfrf78/LZwO6m6mpSgA12E0jugFimOc+cLJWjCSCsMUh3s/GUorUovXy2U9WHdyAUkprRYOa8yhQ4vz6sbAwBYcsMCgFCon/1Eq8W3VIcqp08gX/pH70U9BpWnFf8x4aQQ7v9FKFvGNqSA5moslPHFf9Fqexd3ofxt1Ug7sp2U/mRV5JYbo8l4aLlPKGg1m5OidTpIKNnOC5rilUoXu7Wjuvr7yRfE90U0IvJMUF1W1tFX42Crn9iZGVv1LQCh9LneJYWw32YRKnRqLYqeAwgDoHNncr/pvE10vLExYFZH7GDsmEnv4NbwPADAfQndhZDiK/88npTWVkVEu2y6a46Dj0X+5x9p3JgcEbcjz/2edij8TgvXIc3Qrsd20Y5AzVbi+x8qxajT+voIJdu0Cxkh330vXFteL7hGr1qLVsRNTohxZduH8jz9RRxaNu5H48ujiDBwQqNz4TuV4Xvy8Qv190OrijKnnqDxc/KhaMuznejvpp7qwK6DTRJS7nhYv5Jc7saFi364eJRcct4pxMFic2Mah89/E6F41//8GAZBYnfF7Eca71NUxtCVIWSIV3YUl8YtKkYHrVIOhy/tSweEE5qSkaa0JqN9uiO0Ql8iNTAMwzDfLvoyF2WopUdFRWHo0KGYO3cunJ2d0302V65c+PXXX+Hk5IQiRYpg48aNcHNzy3RlbocJZT28LCmb+y6Ilmxdk1wY7Bxd1Z9rrRfK38cY+r6Ji1D4MKC2Om3heKHUjtNQoJKLkbI+95pQaKasIeUk4p1QbsxoARlN2pL/9JjFwoXilIa70cMHQs6126RMtagulKCaDelgdXJBcsux7CKiCuXPR6Mm5fBzwiYyTN41EQrYsC7UbUejSPG+o7o0rUUQlRMZKFbtTbqTu0ePPxqp3otWZMt1pkg6KbH3XZ1JToehQkHf9hsdFF38q1CSW3Sm1f26/mSQ7Rp8EgBwaRr1Vxlr0ZgdfibZxpdEuxSbQIeurTSiIdWdL/IPLk8r2p2Wi92TXAWo7a1cRJ7ClkmY/LswmoxukptZs2nCzc17j4ZRqYrc8+8bMgqP7aZdj5SL3a68ojF5ea+IDFVuCa3KNyonPr+YTIr1OhfKc9VHtN+KmzRO++wWrmWvNIyZ9XdEfYKH04nZwCOkGa+8JRRmxWq6zXrYagcAQL6yi9RpeUZ0AABEr4lQp5VdT7ssBduIPna5Q+1sZiYMigZFqG9Kq1yDqvuR8n/1AbWPhaUYa+5/kSHVd40IxRp0h/qmWUnxd9phSTls3ioM1mSNu0HapP/TkiVM9WQVhmEYhvl20Ze5KENDYNWqVYiPj8eMGTPUaV27dkW3bt0+e9bGxgaTJ0/GkCFDoFAoULNmTfTp0yfTlSlXTyjH/9tDK9G1KwtF4+8l5D6hqUQn/C5WYIuOIiXyboJYnf4uFyksI4YIBb7xGFLQD5Wmg6SbGos86zWUl+uqqC4hq0j5regvVlXdC39AnKqajx9pHGItLxTdjY3ILWLPQ1FOUFMHkj2aVugnXRSfX8dTfSuoDj83nk6GScqNy01dLlK9D1J0puVmol1Cl5A7R8wFsTob7dZJnXbPTHR7UjLJS6xMUXrsSog2uPBQI1Soqm71B9MdBmeeizo6jaX7EYZVIGV95OTGAIBHu+iw9U+ThMJYeiAZMFVUOyE3Y2gH51YMWV/XVHeddQmiNlv+g1CofQeSAj/pkVBuX2/YoU5betBL/Xl7hHjvuHBaYU/2For1qn9JKVWaUD3MVX/IMzUOE8/MJQzEEuVprFxTRemMuKJxc3UpUvCHzxdjZMc4cuXqvE0Yors60w7E0zjVHQ/t66jTeo6i7w2cRbsZKjTuR4gS9Yi4Rjdp1/zDQPUu1I575tDY95gqxmeHTqTAbwsSBkBDR+r3KWeEvENtqd5b7lFb7Hwo8t+5T32zesppAMC07WSIdykpDofXXBcHy4ri70GRSHLOPtbd0omxQcbPMAzDMIyU6MtclKl7BOSi5MBtAABlNVJKlVHCVcIwmpSq0X60kt+qqFhp7H6ElHrXIkJR23SOfO6rlBY90sCeXBi2aoS9fKVy6fh9C62cV/5OKJuOAaSk5K0qVrzf7iWf+sRKVF+H6kKhNNbYRTg9eBkAoEB+ukHWd62Gu9EeUTfTY6TAL18jlFqfQFLUTIOFTM0wo0EPSYGtX1C825azGrfAHhRluo+m9zo4NQIAoNRYka3Yk9xlru0QK/zJlcil5/pg0QbdjtN7vYoT9Y6OJiWwpcbNzWGPRftfH7VKnVZjQX8AwJrGFN8+JeKOvTkpt4HhtJq+u4tQhO+9pUadHi7yHGmjEU3qrShT82KtitZU5lLVbc2vNOLb7/ARh91PhZPB0KE3GQqN/R1EHfrtVqeFnBXRlvoet1anxbwWf0bv7tM4tSpBfRe/ReUSE0/1WbdZtPnSG2TYPlfV7d9NZDwllqd+WO0txnvKuQAAmHVFtIWGXo1//hSGb3IBKjtvefqcpOqmFhVoV6NTCWHE9OhP75+gMl4vD6GIQx2O0N9fHlVI0Y2NqR+qDBC7ME69aZwOqygMidX/Upsc3E9GUwON+ww2NCIXsK/hwsu9qf5fI5+nVuUxOQ++R4BhGG3vEdCXuShb3SxcqZNQHAaWo9VHv++FQhO4lsJN9vqbFPiZR8VqqKUlaUFBcSIt+R9y47nytyjzCoBhM4QCVsia8rxWnfLtvVjDhFOK5mnXnvyX1/bcpP7caY2I9rLJmyInddjsDQD46zfawSg3XZxjePmAfPu9HEgJSgnEU2gUHUR2qLwLAFBtHimoEbmEK8nvARHqtARX2jEYWVWs6G65FKNOi758HABw7IaPOi3RSaX0J9P7R71Uf0T4PKGEtw7SUKinC0WwcSONOwrCxPvM6kGGwDh/UiJTogHZutG5kpujxGr94V3u6rTvK5Dy/O8bITPIioy4fketAQDPd5DxNXGSUDwrBJBiXaCmtfpzMRtRp39G0Z0UXZZVVsmj8XVjljjHMP0SvYNJO1J0D6qiCuUyI0OzrWolP3EtnQfwmiN8/4PzkrK9z5P6ONxd+PYHhGvcw3BFFdkonFxxjB4JYyYm+KQ67apGGFeX7mIlX3GfdkJevxUHfm26065PLdWh4wjyBkoVaSiR7DU1Tz+INk0qQ+/aylHkGXMuF3qXEWMgYh0ZrPNmimcXXKOfkiSVy93DNzR+evWgXbX208S5A+MiZBQsrUcGibaY6IlfJsMwDPPtoi9zUbbaESjdaQMAoK4vrV53KymUj3J5SXNpHUh+6O9VUX6KOpAiUl91u+3MOhQm8nS0OOjod4ryJsRruEA0FMrh0N/JEDgzRpTj/D+SbVJDGCT1y5FSlaykPLdfCuVnQm1ykRkYKAyXPzrTquqA+ZS/oYdQmF0L0m7FxO2inJ0DyHh48E4VeUZjt2HYFFKiDVSrzUoLWk137ykUtSNT76vTRv4mDvn+/ZgMKkeNEKCnnwvD58ZJeocS9YRyd/8MpS0bINrPdzgp/wYv6B2VKmXe8AUpxFM3C1/z4lakwHdZLF6ofzvqQzuN3YH/tdoCAFh8sIs6rYK16JPZV8jF6PRJIadoDVIwO5ai+oSoIkz9G0n9Vae4kHPgJCmiF0dSW9QcI763b0Cr8omq8xuRUw+q06ysxFgrN4XurphThyI1tWwilPV5O+nAbmi0aJ+fqlF96m8RfbffK0ad9lYj1OzYcDF+B2mcl1h8Q7RBzEf61emmcktytKX38vqTjJTe9UX6+0TKs/NPUebeiTTAWi0Vhp/JeTKqNe8RKKoKNVrVhoyZvauFVXlmARlz/ufE+Dl6lNoWCo3L8BpT3XY2awhtuBGTehWmgnX2XIVhsi+8I8AwjLY7AvoyF2WrHYHGI4SCekQjasv62WKltZTGRVVG226pPxuqVsS7liNFZPZuodyMqkoRSnqOFAqhwVta+jbydFB/NjMUyp3RfZLttV/4w2+bRApd5yHi8O7JA8CdQOHH/VM4rVSvdhErscPCSAEzNRf10VT+1/hpmopCaauVn9wjZtiK76vYkALqNVfsMswfSIqhppLdaZxY6dd0qznyk7jjoPxPdIi10nfiHTUNgU4lyAjZMFIYDXGRdD/C/QJtAAAHfySjyH2WalV+cAl12r+r6XAzXER/1qtEBleb4kI5LDuf5BWtLuq75gy1T5PK9Dl/XhG9aeIE6rsTvwvl18KYnvNqkfLeCWilcg/74RAZCnHzxXmJunPJdz1WId7hyihq07W3SYGd7ivKH7siRp2Wu7JQxustoIPw53eLlfortzTCzzahvnOdLxRd/8PU75d9RDllB/6rTmvgLSL/1J1PfbOkJ42lJzGinna5SM4j1Z/GmzdkPB1Xhc7VvOzNQOMSsrbFVYd3V9Ful7KUNQCg1TJ6boiH6LulpuQ6lhIBCQAeHBM7GA9jScE3fCnavtYSev9t3mKMDy4PDDwojIJ3u6mcF3U0LuDTEn3xy2QYhmG+XfRlLsrUjsCiRYuwb5+44KhRo0YYPXo0xo4di/Pnz8PcXCgsvr6+cHNzQ3BwMGbNmoXk5GRUrFgRU6dOVd9KnBHflf5e/NukiTpNaUlKba3WYnVb8yIwnzJCEf4+jNwZKlmL76fU0vAFjyDF00N1rqDlHgphuaW5UOQMNDquw15rAIBCw42iTCFqrpRwp4okynRtgrhzQNGzojptfDOSveaWWK2+OIL85i9dFu4/wzTe4dYCsYKctwcdxG1VlpSt9XuFgmcQQ2X/0F/0xbXX1N7HrgnFs34FjSg8tlTOrGMqV59rpGQnFRGKWntXUlpL5BaNsCSMFMfdHclo2qS6m2F1n9PqtJTDoj+vIMXyVICoh+aFar9cIiXwgcqd5KgnrRBXWyPkxD2g1f0J3UX+SfupPikHywHg3DWhKDegS59x9qbI06oaKce/aByMrVlfGD4uv1Hf3X8rxt+CunT4e90d0c4hkeQmlXJGAADezw8DAEzfRsKX3RTv+OghyZ7nIZRj/8O0g5FL44B7kkrXf7/5rjrNuqcYD8NqUVsErBcPTvLWuFyuGxkX+caKA+WarkEJt0WbJmuE7SxdXbxX04JU9soQGksGt0QbBE2m9YOUfl/X7x912o8bqwMA1lzSOINzkYzpDT+mGDPUZu7T1B9xf5Z2qyb33u5J9f+SuVtrVR6T8+AdAYZhtN0R0Je5KENDIDQ0FAsWLMC6detgYGCA/v37o2fPnliwYAFWrVoFOzu7VM83atQIf/zxB0qVKoXhw4ejYcOG6NSp0xdKT03RqpMBUPhBANj4s8oX2pPCF1YqTcpSqdxCyfQpQ8qL3xmhUD9YHaFO6ztO1HNFMCk2z2YtU3+etV9EN7r2mgyP/UdF2YYPSIlp0Ve4Bp2PpOd6VyTZS8OF8vP2PqV1VK1U+1YkNx7P7dbqz3H/CCXc8Cl9r6gtXE1W9yBF/1iUytVGw1jZNJwuhEo5tPx7AClgY0JU/uwK6uZ3i4Rvu7I3KbzJZ8n1I1G1MlyyOu1QDCon3EZ2aBxOHlpeuFP1G0i7Ne5j6czC2YdCYfyxNr3XnLNC6Y1dTuEvzfuJ3YojnUjZrjuQdjr6+ImV5YsaBk7KYdiOA2nVOXCrkNNeIxLOdnK1x+mh4vvnH6kBN94VbbX5KD1nZkN9q1Tpzq2rkzVYI58YF64FySDteliMuQK5Sdk+e4XaPHyQGEPzr1LdAi8IOcmHaUep3vdiFyVsJIVzTa5If2Mth4jPR66TkduovDAuSuamOl5VtdXkmmSs+Zwkwzdy2hUAQGJP2ikyCBM7TtV9KDLUxd9F3Q4uJ2NtewQZD62LqYzqDfT93h5irGi6NPXcLr4vXITq/eI5GUU9a5JxOq565kMOp8XDd6l/fItZZc8fXyb7woYAwzDaGgL6Mhdl6Bpka2uLMWPGqFf1S5UqhcjISERGRmLChAmIjIyEm5sbfH19YWhoiKSkJLx79w5JSUmIj4+HmZlZBhII6/+JePHjqpGiMUgVc7zu76RUXdlOPumvW4kDxo81LhyLiBAKRq0hdNbg2FOhgBje1Iil7kEGSkrYxv1BpIAm/nUOAGDs5aRO2/8HyU7RyGc8ooPMIQNjAKRWglr9JpTDnfPIr/vqelJgK6v8phMrUJpDBdFuA3+gQ8drF1oDAGrkowOn7+fQAePbqtXrSf/QyvCz28Ig0fTxbjxLxMG/Hk3PNRhEsk1UblJ1bEmJ/F8/EQmm4AhSHBdcF8rdwGmkODvbaZyDKCfK8ZqlToJvT2HY7B9DUZMi5gtXr9q36UyHdXPaHVm1ThUN6Df6foXqPMXRp9TvnTqTkp0SzebaD/SOG1ShYfc8ImMmLlH00+Y+Meo0b1862Oo9Vowvew1XnJ86iHFh1JjOAxi+EArzgyvkjpYrH9W36nJhsE3bSbtdS1qJfq/Xx0Gd1ninaLMzIZRWdx2da9kTIpT9owPJOPU5Ltoql0bM4lO7xPsMSyDl/95dMhSMeoh+NAym6ERdfxRGxuZB59VpTnPEboK5MY2FpaupjzfWEuWbaazuz7smdnNm1aY8hpuE4RcFILGuMDSSNMIAF7XS3c3CGhd9MwzDMMx/gr7MRRkaAmXKlFF/joiIQFBQEP7880+cPXsWkydPhoWFBQYNGoRt27ahc+fOmDhxIry9vWFlZYUiRYqgRYsWma6MTw2h3FVaSUqFZ3Wh3OXaSivIXebT7ayeRWMAADsekPEwuK1QsAbtIUWjj5NQXl43IKW9OEX9RO8yQrEq2pNWnVuOrQkA+D6Uyqn8nVB6twaSwTDYlVxfJpwXSvqFhzQC/vlJrHSffU7KbYUJtPq9f4F4x9ad6PKrhSOEAjovL63OdtsslNYdPUjB2naQlPAeLUW7tStOuwi9ngllPfRPa3VazZ/FSr5pGTIoHn6nYUi9Ut3dcIvaou00sSPjXYbqfVy1QzHnANVhW1HajVjeJEZ80NhzWnxK5KlTgVaDX3qLMfbqlcY9AW70jl0vCyOtvPMJddrcQHEu4a2C2vmE6r6Gly+onH0R9P2kOqJd6thS+zz/KMruuoLetf2PpMCffS7Sb2wj42DXEaEcey2k1e2Rg8R7z/ybQmae/4HeseoMsVMyfQJdvrZ9mVDwfTXOk0RMECsIv5dL+++mbGVhzFx+RSvohVW7EAPKkYK+S3U3w4Tq1I5/5yOjPMXl6VGJYuq0TiVUt0P/Rcblin/FmGvcmHYtjOzJkPL3FWXm1rgA7kTKvQYa4V6VtmKMH1mbFykDoqk3nRGYntdB/dmb/ry/CiODbBP/gGEYhsmh6MtclOmoQbdv38agQYMwbNgwtG/fPtV3hw4dwq5du9RGwIoVK1CkSBFMnz4diYmJCAgIyFRlep4Qit7EGqS8tOgpVoNdRpHLyeF/aLXdKrf4nLAnQp1m+FwoRIp6RdRptVrk+azsTjtIEbaxEQrjk8vkxuLeVCg0Zx+QQrPCXeQPuECrtHEJVJ/I38QtubeOkHtT1+PC9ef8H7T6qunfY6A6aNltPB3ITImKM24fKdaFC4t6aPaY5pmGSJUcw9ek6Dr3E4eXrTQO1Y6pKgyBPBpHN3ZG0H/MjYUAGzMStPmeUP7Ka5zP6F5KyGk8hlaal40lZXPAn8I4OzyQFNSma4VhYraNDiKf3C/ee+1tMuaWr6E8N2eL72usJeMrdx7RX3msqAFu/SvqYRJOSnvD/gXUnx+8E8ZO9DNS0D8sDAcADF1Lq/vnX1JbhI8V/Wk2hC6sK1ZAyLyxVyNUqp1QdG+NJReZmzH0fQVrYSCUm0RppvtEJKsqM+gswcU/Rd3H+9PYfK4RDWjRYfEOdoXIcHt1WOQxukV3M6Rch23ag5T6j8dpd+ntmbMAgOGbWqrTcpuKMaK5+7FUFZGoS0n6u5jVnc4DGBcR7es5ngyK86poSHHvafy8eSM+BzSjPpxzhgyKW2OXqD9/eEgher+Glx//SvX/fLnaaFUek/Ng1yCGYbR1DdKXuShTUYPOnz+P4cOHY9y4cfDw8MCtW7cQERGB5s1FfHOlUgljY2OEh4ejbNmyKFZMKAWdO3fGDz/8kOnKpLg27HtMymRCY1FWygomADTW8Nd+GS+UpB6zyY86YKhQuA+NJ0Xk+UfyW27fOBgAUGh8K/X3pWyEcti5IymW8UlipfbgdVJKfzAnAyCFm/6kuHRe0wEAkKSkVd6zB4Xs22spdGTTv6nMabVjAAA9/6D6lqgmFDBLS1JaF7uI54aH0s7CFEdyEfktt3DTuLqWdhZO3xDvY/gH7aj8eEi06QMKp4+tEeRW81plKzUvSQbFAmfxPtV/IPcm+xEiT4321uo0a1MytMZ6in5q8QO9q7GJKLPlTFJQG/ZOqe8btPufUPobtqMyDQ3EMFUsuaRO+3mnWDZuWICGcOUbYowoatjDNFicLTl+glbO3V1F+z5eeE+dlsvXEQCw9OcIddqSRbRr9O8IYQAUpiRcOibecb/GodkPSUKOUknt6BtM7xD1lyi/kAftNszxdQAAeA+jlfHhP4ttKic7MrjeaBia24sJw3CKM7XzkD2inX9e7aBOOxIpjKoZqrEFAHXfk1EUurAxAGD1v1R2czvRx5q3LDcuJBT3Zx8NERotZCf3cVZ/n/RQjL+6tlTfI/+KfrCwoLIv9Ev53hiVFoq/2TbO9Hcc26YzdIWhgZ7sxzIMwzDfLPoyF2VoCERFRWHo0KGYO3cunJ2FAqBUKvHLL7+gbt26sLCwwJYtW9C+fXuULVsWM2fOxIsXL5A/f34cOXIEVapUyUACMbi8WHXstIVccdo4i9XJuU6knFTwvKj+bNVDKIQL3lKe31YIZetVvEYIStXq9huFAfaebAAA+CGEFJXQX0XIzJOPaTU5z0iVNWhMyninskIx+vM6rdRXmtNV/blkbvF9w52kZRs9EErbkFBSEje4kkLtpYpO1LQhyXmtqnvNiqQspYRvf3iOlMABT+m9w32Ekt0ilnZCCuYV7914Dflb/H5LFLR9OUUK6jCI2nfrSVHOrfxU9sHHQpkv0oJcX+KTRH/dpSZDx6uUJ6S/qOfsWFISg9cLQ2rrfTKUkoqLtNi/DmG1uI8NRQPo/Mb1GGEo/LmPDozHqa7R7XaM+sH4vlhtd2xvA1QXxo5dLmrTJ+/FKnmSg7U6LfFaDABguoYh+c8L2gGyyi3+kOc70Wr7VjuhZC+5QX8+/cqJtjj7PEadls+SdgdWzhH17Pa3RnQh1TkSE3c6yzLvd+Ge4z2Dxma5vPTeNnlE+QPWkmG8apZovzV3aEfl4n1R7/iaVM7bBdvVn1fUaQcAyK/RPt1UB3oH1iPj6YfKwuhc8+9LdHJQ7SSVoXcIjRZ5hrbcSXV0qCY+9NQ4v/JGjKkZV3KjrvCswoWn9CMZMkt3kYxTDEddERkZiVGjRuHly5coUaIEZs+eDUtLyzSfDQkJwYoVK7B27do0v2cYhmFyBrqei6QiQ9egqVOnYvv27epVfgDo2rUrkpOTsXHjRiQmJsLd3R3/+9//AAA7d+7EypUrYWRkhOLFi2Py5MmwsbH5UvGpSFYKN4zdD+jm0h8Cxe5A8fK0S9CvPCnZE1cKhdLoDvmuJzUVdXWrRq92bKI4rFnen1blL//vFAnvWRcAkL8IKViuJUXZx+9rxOX3IheJouW3AgCaruijTutSQnw/6Tgp1imXnn1nSwrmq1nH1J9zDW0s3qsuKWArVGEbjdfQ7bXmw4VRlaQRznRLW9oR+FMVAce7NLlfFLUSilq1zrTq3ORHoXham5KhtPMCDVjFQ9G+RZ3IPWVh/RgAwMiztBvxSy2RNucaKbzDKpCB8+NJoaBWsCdl82OyUEw1LjXGT9WEwTD3KpVz8iS1hZXq3MFfHWLUae5dhNLvPY2U6I8aYVxT7hGIiqM2n3lGKG+1i1ED2qoU4W0XyR2oUCHKU9hCPBs68qI6bdM+YVSNPG2tTkuJyvR0CoVPTUiksZLLQbi2aUaGSuor+lN5ldyFfvlRjJuoD1SHajZkNM1XHdCeUpP63WtADABg7yqqj7vKBcu7Pr3rP6/obyjIXRwO9z5Bh+cvPRCKefNyGuFeH5mmej8A6F6Zdorm9xR3MyzdW0udlnJQ21RjMeSXyzSWLt0U35coSWPu8SMaI7cHuUAbYhWHU/0/j0kzrcobNGgQ2rRpAw8PDyxevBhxcXEYNWpUqmeSk5OxZs0aLF++HGXLlsX69eu1ksn8t7BrEMMw2roG6XoukopsdbPwshviptY6Grehdm1DhxRzDxORZt7OvaJOqzpDuG6cO08Kj/E/tETt+5NwtViwktxTunqLVeutczRuS7UVClhBV/IBMTYhxTLihlBMBzQj5TnwmlCs3sZS2uvfxC24fxymMFEpxgwArFNFzRl2mJTe8fWFcjg6iFa3m6iMGFuNFdux1WhlvWptEdmlzTIaqNv67QcA3LnUXJ32fahQKK8+Ia3szX46q1C6hziMnJhM72pvLtoyeAQZSnn8GgEATnQlg6vWr7QCfXC4qJtmaM7RocIQKJiX2ueyKiR+lZL0nG0u6rsyecTnRRvIELgyVfRNvc1kkH38qBGDvrJoo7AIUiyfP1dFDRpCZd9U3bnQaT61hWlxWtk1UiU7aax49ykj+mb8OVJkJ9QShsug36hsG0cykCytREEHWtI7dj4m6nh1L+0sJB0X43jGDkd12r1YeodDT8R4sDKl+uxQnVsp/yP14ZB+on3W/UP9Ubk45TmnOo5xqT/Vd2CIGBeaNwsvrRcDAPj5HxqbW3utU3/O31LE958wgtps9S3xt/QomMbFcG8a76/iRRuMrEJ/0y6qHT/3spS2pDPdqxH3YCO04X3iiVT/T4qrgdjY2M+ey5MnD/LkyfNZuiYKhQJOTk44e/YsjI2NERUVhZ49e+LIkSOpnrt9+zbWrFmDRo0aYf369WwI6DlsCDAMo60h8OlcZGncSKvypCJbGQKll4mg73cGky/zipvCZedwFCnJo6vQqvOSG0IpefCOlMSpqpXq3rtJoUn8R6y6Ki1I0SqucfPrn65CQWuhEd//7RWx6tq0Dbm7BNQQsgeHkOI3X+Oyqf6nxO5Hbo3V9oV1RX1+/oeUjmcfacX36shDAABjI1KgTO2EC47TeHLpOT1P7JTc2E7uVrdj6TxA3Zo7AAB25Ruq0xJaCLeSTV1oF6WX3+dKUUc/co35oFIOd50mRTawh1CIt9ynfrgWo1ot1jAi7u2n1W2DctYAgHz56V23tRJt9Z0ZKa01O4tDrLv+oJ2jQhY0LDscEen3/iFj7n9e4vtVF6g+mz1Ef3kftFanafqpr2woZPc/SX13orUw/MqoQoICQNI9UrKvnhM7RX6nqT9/U0WTtTCmsFN25VeK9ypKh4pbTyOXnpQ2CppJhm3oZlFP5760SxB3SVxIp1SSPFMTUrxNh4jV8oSldEFCg/miv0/voHG4Z5IY517bacxp7nQsriee9fQng2vHL2L8uToFqdPG7hCBAVLuCwCANu3p0LGig3D/ue9Lf7Mjz4gxeeMN7bL0KyPGn/9E2skwiCNDoMEw2tlZ46Ldj2VcYmolbtXSf7Bo0aLPnvP19cWwYcPSLSs6OhodO3bEyZOivRMTE1G9enVcvXo1zefPnDmDRYsWsSGg57AhwDCMtobAp3ORhbF25UlFtnJgSogXyt3V13QrapeSQsGfvjJGnfaoBCn9NfKJlehrz+hVTFSLnBNcyUXmQFmh9H/QWAF1KUAKWMOh4tlkG1JAq7YUCmM+M1qJH3VWrHLnNknG7w2EsnbvLSmbj1eJg6h2PUuo01JuztW80TfiHdV3+D6hbPr+RnLiS1gDAEK3k3KXeE+495QdZa1OWzeKlLueG4SDfUzC5wdUXsVTWuvhwsjYeYyUzf5lqa08mgs5tiPI4AhUGQCv4knew8cif8vKtNLsM4wU/AnrhOKeZE2G1LKbYvX60B1SEgdOEmc6Qp9RfWZprHgXHCz6oYs7yXayFfX9UIXa/upr0ab+td/By0G4h5VeSuE63eeJcfN7f1JGyziKqEEBm8ur06Z4k6HZdLdotw1ulKfVfmGYPHxARo+ltwcAQJFE73DgOvVxfpVbWIILKbyHn4jxcG09GRRP40RbaV7+9Z0ZlZnyaUFINXVak2FiZ+v3adTOvmFinJYtTnmv3aZ+6vZKfJ/LicZ7MSvxji9v+6rTSgYI4/NqUzKqd+5Qf0SH7aL9J18gA2f7SdFmF4bT7kerveJ9bNtYobyt2B1JcbsCgM3nNMJfaecZBEMDo1T/792792eRzgB8thuwb98+TJ8+PVWag4PDZ/kMNEN1MQzDMEwafDoXZVeylSFwY6iYYLsfp8g8y+sLRbhgfVKMNtzVcHu4KhQdm/yUplDpPpo3v844JRRZWztSiDVdkBRVhDIWv5JWQy9Zisuf8rnRqvO538Vq54kVVohRFb//MSm/Kf73MzWitYw6JxS0O2+pucOjafV/TDWxWqrMQ2kjmwolcd59UjqKBDQGADjYkLvQ9wfpfVL8uMO8afW/+mSRv0gbKnvXIaGA5daI+d/lb/r+4wehwLUrRe1joIqHe/0ZDeyEBNHQmsbB/HAy0vKrLi7WdLFKif70ePJeeq894iK5oMdUn5RD4AAwu65QULttI0V3qqNYge4+6Lo6zdLLAYA4QzHxhDgI3bgKjQvHfGkocIWsAQDnnmvEUtXYJEtxQdrzkPp4vmo13bQBZVmtirSzotsWddrzJDL8PjRvCwAIGEkKtVthMYBqbySF+OOCCADAd/60a3HvDinzV4YI96aqc6it1v0i2j8smtp+r7sos9V+GnNNqtK4ObpZGDF9+1F9chmJv7G+p8h4muUj2mzLfRpnE87T32eS6tB25xJ0buBoBVF33zAaFy/ni7MuBglJCFWlNZ5NN1srL5JMbfn0gFZmXIAAoGXLlmjZsmWqtBTXoKSkJBgZGeH58+ef3abOMAzDMJ+iL4eFs1Utq7cWB3qbjqfV9CabrAEAC5qTO0v/paTQfQgU5wo6b6FQoN0WCKWlSiOa/Gc1E8qxlTEpeT2aU0hNgw5ihdVxflt12uDyYmXY3px2DsYtFcqoy2hSku2akNL2VBVq9PwjUpZS9MrIqfvUaT9upkMjtf8Q76i0oDLnrRD13TeJlClrM6GgD9JwS5rQgOqWEv/f4296b5MQ8Y4Pm9IhacsiottL0F1lKGFFyujuLsL3JUHjste9c4Q7iPc4cgGZN1YsDYcUqa5OM/PRuHnYXbTfgDG0wv7qhlBA7cd5qtNW3xb9Nas27X68LE2K56wr4n0cK1Df5SslXD2GB/ZUp71OEO9w8l8a1uXzUpvODBLpSlMyenK1Fv0ZNDNCnWbYj9x7KhdRRa06SGWG1RD5C2ic37irMnDyN6HzGQYXyG3L/0ehcK+8Sm4+MwYImfYjycj9OECMw18b0HgPf0EKfs1VwgAwfE3f+x0TYy2fDbWZg5Vo86Gka2Pcj3Qw+MRGMYb8z1HZJasK42zIxqbqtBK5xTveIW8g5MlDf39Jqh2QZg3Iter+ZRErufwPtEtgNUBUpAxdlYFjE+guCSMdXsFooMOfNRMTEzg6OiIoKAitW7fGrl274OKi5ZYFwzAM882jy7kIkC6CXbYyBGqMFqvAPUqR4ljBWigq12KMMeegWLU1O09x4GfvFTewThlPSs62xdYAgF5/keK4IJlWPv8NEqvFYzeR68tUlZJ4c/1jdZpvNbHyV6wsrRbPrydWp7dNMoN/uJCjeUbA46RQnF6YU9Na2ojP7VbSbbHLllKeMu2EcncvgpSy5H/FanGrn8gQ8OwplDfNiDtjp1FbWTQSSroFBSxC4DbhdvMkjgyGP5JpZT2FGbXpHVOU539eaew2lBXK6qP39F6234nD23ivwIkTwhWn/T5SElMi3EARQ+9VTCitlhq++9W+EyvnG+9Y4JrKr7xcHtrNSblky/ARKb/z9ouQrdPmUDt6D7YGAHSomqSOIHQnltrU8KloK80L15JrCzcpr3EUcjUuiRT870zF5xAzKufuU1F234ZUTli0eK5UPzps3k7jIPKg3mJcGbzXCJuq2oV6+1bDHa20KLv3Mmp7zxYaEZ0+CsW7SF1rddrfHjEAgNqryQAce5jkNG8v+rtAHzqzMO2i+D4siMZP7nwOAIC1YfSuoaXETkgBW+D238KIi7tMf2s/LhF5FuyiqGKKZDHWWnUjY/jvneLv5p8rQHI+Md4NmtAlgXUa0I6Ltuh6FSYgIABjxozB0qVLUbBgQfz2228AgE2bNiE6OhojRozQqTyGYRhG/9H1XDRp0iR0795dHcFuyZIlGUawywzZ6rDwhPMi1NK6o6QEdVAtvpkZUTWj4qhxU5Ti0xoXIzUoL5SlyTVJyXHfoopf356UyXaDye9baSGUnzuryff6wGNhcAwM1IhVf024MOzXcM3ovo8UnppFhELYpywp3g/eCmV+/Chyf/hpBrkXpLzDtHmUR2kp6rNoBL3ro3einN8vaUQXKkkK34mHQole3SxGneYRIOpT0YMORl87Jt57vYb+cjSKVslXbxWKuV1Neq/Xy8XqbVJJa3WawUdRdvXetMx7/ii1ef+Ooj6l89Bug3sRUd8fz5DSemK3qI/hK1Ks500iw23tHaFQn71KY8DTUfRx0Pdn1GnGZYQyn1SC6jhvKBlSt96Ittx9l9rv6VRxRsBgQE11muI1GSELuov6jhxN/u5VBgilt00xOryc4ubzm8aK/6FbpFAPcRRnGo5oHHofqgq1Ws2G2mfWFZF/61nqd4NLNG72zBQKc+sAjRiyKecSNHzXu/iI9m1gT++S0o4AcOa0SA8aTG2+9Kb4fk8wtfOiLmIsnNAYH7tH3VZ/TuwizlYY/U3GubJ1KQDAcBcqO8UNr+tqUvjzFyPj883W++rPd3b2gjYocSPV/w1Q4QtPMkza8GFhhmG0PSz86Vz0NrZwtoxgl60MAYZhGIZhGIb51li4cGG2jGCXrVyDGIZhGIZhGOZbI7tGsGNDgGEYhmEYhmEkJLtGsNNdqA6GYRiGYRiGYXSKZgQ7ADqNYMeGAMMwDMMwDMNkYwICArB161a0atUK4eHh+OGHHwCICHbz58//6nL5sDDDMAzDMAzD5EB4R4BhGIZhGIZhciBsCDAMwzAMwzBMDoQNAYZhGIZhGIbJgbAhwDAMwzAMwzA5kGx1j8CePXuwdOlSKBQK+Pj4oEePHhnm6dWrF16+fAljY/EqkydPRrVq1T577t27d+jatSuWLVuGIkWKIDQ0FNOnT0d8fDxatmwJPz+/DPOMHTsW58+fh7m5OQBxG5ybm5v6+UWLFmHfvn0AgEaNGmH06NEZykkrT0Zy5s+fjwMHDsDAwAAdO3ZEnz59MpSTVp6M5ADAzJkz8fr1a8yYMQM3btzA+PHj8e7dOzg6OmLSpEnqdv9SnkWLFmH79u3q2LmdO3f+rF/T6sOHDx+mOxbSyjNnzpwvjoWjR49i0aJFiIuLQ4MGDTB+/PgM2yytPOm1WWBgIDZs2KDO//jxY7Rt2xbNmjX7opwv5fnw4UO6fbN7926sWLECAODi4gJ/f/8M+yetPBn1z4oVK7B9+3aYmpqiVatWGDJkSLpy0no+M2OAYbITPBdlv7kIyPp8xHORICfORV/Kw/NRGiizCU+fPlW6uroqX79+rXz//r2ydevWytu3b6ebJzk5WVm/fn2lQqFI97mLFy8qPT09lZUqVVI+evRI+eHDB2WjRo2UDx8+VCoUCmXfvn2Vx48fTzePUqlUenp6Kp89e5amjJCQEGWXLl2U8fHxyoSEBGWvXr2Ue/bsSVdOWnkOHjyYrpwzZ84ou3btqlQoFMoPHz4oXV1dlTdu3EhXTlp57t69m64cpVKpDA0NVTo5OSn9/f2VSqVS6eHhobxw4YJSqVQqx44dq9y4cWOGeQYNGqT8559/vigjrT7MaCyklSe9sfDw4UNlgwYNlFFRUcqEhARlt27dlMePH0+3zb6UJ6M2S+Hff/9Vurm5KSMjIzMca5/mefnyZbpy4uLilLVr11a+fPlSqVAolB07dlSGhISk2z9fypNe/4SEhCg9PT2Vb9++VSYmJioHDRqkPHDgwBflfOn5jMYAw2QneC7KfnORUpn1+YjnIkFOnIvSy8Pz0edkG9eg0NBQ1K1bF9bW1rCwsEDz5s2xf//+dPPcu3cPBgYGGDBgANq0aZPKmtVk69atCAgIUN/CdvnyZRQvXhxFixaFsbExWrdu/ZmsT/PExcUhMjISEyZMQOvWrbFgwQIkJyern7e1tcWYMWNgamoKExMTlCpVChEREenKSStPZGRkunLq1KmDdevWwdjYGC9fvkRSUhJiY2PTlZNWHjMzs3TlxMTEYO7cuRg8eDAA4MmTJ/j48SOqV68OAPDy8vqszT7NAwBXr17FypUr0bp1a0yePBnx8fEZ9mFGYyGtPOmNhUOHDqFVq1YoUKAATExMMHfuXJibm6fbZmnlKV++fLptpsnEiRPh5+eHR48eZTjWPs2TK1eudOUkJSUhOTkZHz58QGJiIhITE2FsbJxu/6SVx8zMLN3+uX79Oho0aAArKysYGRmhYcOGWL9+/RflpPX84cOHMxwDDJOd4Lkoe81FQNbnI56LiJw4F30pD89HaZNtDIHo6GjY2tqq/29nZ4dnz56lmyc2NhbOzs5YvHgx1qxZg82bNyMkJOSz56ZNmwZHR8csyfo0z8uXL1G3bl388ssv2Lp1K8LDw7Ft2zb192XKlFEPyIiICAQFBcHAwCBdOWnladiwYbpyAHHD3IIFC+Dh4QFnZ+dMvc+neZKSktKV8/PPP8PPz0+9ffapDFtb289kfJrn/fv3qFChAvz9/bFz507ExsZiyZIlqfKk1YeRkZHpvk9aefbv3//FsfDgwQMkJSWhX79+aNOmDf78888M2yytPPHx8Rn2DSAUiY8fP6Jly5aZHteaeTIaa1ZWVhgxYgRatmwJFxcXFC5cGCYmJun2T1p5ypUrl27/VKpUCcHBwYiJiUF8fDyOHj0KY2PjL8pJ6/mnT59mOAYYJjvBc1H2mouArM9HPBcJcupc9KU8PB+lTbYxBJRp3GtmYGCQbp4aNWpg1qxZsLCwgI2NDTp27IgTJ05IIqto0aJYvHgx8uXLB3Nzc3h7e6cp6/bt2+jbty/8/f1RrFixTMnRzFOyZMlMyRk+fDjCwsIQFRWFiIiITMnRzBMWFvZFOYGBgShYsCCcnZ3VeTNqs7TyWFpaYuXKlShevDiMjY3Rt2/fz94lrT5csGBBurLSyvPmzZsvjoWkpCSEhYXh119/xdatW3HlyhU8fvw4XRlp5QkPD89U32zevBl9+vTJVLullSejsXbz5k1s374dx44dQ3BwMAwNDdNUOjTlpJVn8+bN6faPs7MzvLy84O3tjf79+6NWrVpISkr6opy0njc3N89wDDBMdoLnouwzFwFZn494LiJy6lz0pTw8H6VNtjEE7O3t8eLFC/X/o6Oj1VuhXyI8PBxhYWHq/yuVyjQPr+pC1q1bt3DgwIF0ZZ0/fx4+Pj4YOXIk2rdvnyk5n+bJSM7du3dx48YNAIC5uTnc3d1x5syZdOWklScoKOiLcoKCghASEoK2bdtiwYIFOHr0KAIDA1PJeP78eSoZaeUZO3ZsqtWDtNosrT4sXLhwuu+TVp6bN29+cSzkz58fzs7OsLGxQa5cudC0aVOEhISkKyOtPDt37sxwDCQkJODcuXNo0qQJgMyNtU/zZDQGgoOD4ezsjHz58sHU1BReXl6fjYFP+yetPCdOnEi3f969ewc3Nzfs2bMH69evh7m5+Wd9oyknredtbGwyHAMMk53guSj7zEVA1ucjnosEOXku+lIeno/SJtsYAvXq1UNYWBhevXqFDx8+4ODBg3BxcUk3z9u3bzFr1izEx8fj3bt32LlzZ5qRBj6lWrVquH//vnrLbe/evRnKUiqV+OWXX/DmzRsoFAps2bIllayoqCgMHToUs2fPhoeHR6bkpJUnIzmPHz/G+PHjkZCQgISEBBw5cgRdu3ZNV05aeWrXrv1FOatXr8bevXuxe/duDB8+HE2aNMH06dNhZmaG8+fPAwB27dqVSkZaeUaNGoVff/0Vjx49glKpxMaNGz/rn7T68Ndff013LKSVx8nJ6YtjwdXVFcHBwYiNjUVSUhJOnTqFFi1apNtmaeVp1qxZun0DiB9OBwcHWFhYZHqsfZonozFQvnx5hIaGIi4uDkqlEkePHkWdOnXS7Z+08pQuXTrd/nn8+DGGDh2KxMREvH37FoGBgejYseMX5aT1fPv27TMcAwyTneC5KPvMRUDW5yOeiwQ5eS76Uh6ej9Im25hC9vb28PPzQ69evaBQKNCxY0dUrVo13Tyurq64dOkS2rVrh+TkZHTv3h01atTIUJaZmRlmzJiBYcOGIT4+Ho0aNUKLFi3SzVO+fHkMHDgQ3bp1Q2JiItzd3eHp6an+ftWqVYiPj8eMGTPUaV27dk1XzpfypCenUaNG6nc2MjKCu7s7PDw8YGNj80U5aeXx9fXFd99990U5aTF79myMHz8e79+/R8WKFdGrV690n7exscHkyZMxZMgQKBQK1KxZU73lmEJafVirVq10x0JaeXr37g2FQpHmWKhWrRr69++P7t27Q6FQoH79+ujWrRtKliz5xTZLK4+3tzeMjY3TbbNHjx6hQIEC6v9nZqx9miejsdagQQNcv34dXl5eMDExQZUqVTBw4EC4ubl9sX/SyvPTTz+hbt26X+yf8uXLw93dHW3atEFSUhJ8fHxQq1atL46DtJ6vU6dOhmOAYbITPBdRnuw6FwFZm494LspZc9GX8vB8lDYGyrQcxxiGYRiGYRiG+abJNq5BDMMwDMMwDMPIBxsCDMMwDMMwDJMDYUOAYRiGYRiGYXIgbAgwDMMwDMMwTA6EDQGGYRiGYRiGyYGwIcAwDMMwDMMwORA2BBiGYRiGYRgmB8KGAMMwDMMwDMPkQNgQYBiGYRiGYZgcCBsCDMMwDMMwDJMDYUOAYRiGYRiGYXIgbAgwDMMwDMMwTA6EDQGGYRiGYRiGyYGwIcAwDMMwDMMwORA2BBiGYRiGYRgmB8KGAMMwDMMwDMPkQNgQYBiGYRiGYZgcCBsCDMMwDMMwDJMDYUOAYRiGYRiGYXIgbAgwDMMwDMMwTA6EDQGGYRiGYRiGyYGwIcAwDMMwDMMwORA2BBgAwJkzZ+Dp6ZmpZzds2IANGzZk+FxsbCy6dOmSquz58+dj165d2lRVJ/zxxx/w8PBAmzZt4OPjg4cPH6q/S6k3wzAMIz88H30+H2WlTRgmK7AhwGSZo0ePomnTphk+d/z4cTRq1ChV2ogRI9CuXTuJapY5QkNDsW3bNmzZsgV//fUX3NzcMHbsWPX3adWbYRiGyX7wfMQw2sGGQA7gzJkz6NKlC4YNG4YWLVqgffv2OHr0KPr06YPGjRvjl19+SfX8mDFjMHbsWHTu3BnNmjVDQEAAFAoFALE68f79exQsWDBDuYcPH/7sB3rMmDFYtWoVAKBKlSpYuHAhunbtiiZNmmDNmjXq5wIDA+Hl5YV27drBx8cHd+/eBQDcv38fffr0QZcuXeDq6oohQ4YgPj4eAFC5cmWMGDECzZs3x5UrV75Yr/z582PixImwsrJS1yMyMvKzerdr1w6hoaEAgL///htVqlTBx48fAQDjx4/Hxo0bM2wDhmEYhuD5KDWZnY8AIC4uDsOHD0fbtm3h7e2N+/fvZ/jeDJMRbAjkEK5cuYIhQ4Zg//79yJcvH1asWIHly5djx44d+PPPPxEdHZ3q+Zs3b2L16tUICgrC3bt3sWXLFgDAiRMn4OLiAgBYu3Yt2rdvj27dumHjxo148OABVq9ejWfPniEhIQEPHjxAuXLlvlinhIQEfPfdd9i8eTMWLFiAOXPmID4+HmfPnsWuXbuwceNG7Nq1C/3798ewYcMAAFu3bkW7du2wZcsWHDx4EI8fP8bx48cBAAqFAq6urjhw4ACqVKnyRblly5ZFnTp11HWYPXs2WrRoof5/Sr2bNWuGU6dOAQBOnTqFvHnzIjw8HMnJyTh+/Djc3d2/oicYhmFyNjwfEZmdjwAgKioKPj4+2L17Nzw9PTF69OivaH2GSY3xf10BRh6KFCmCihUrAgCKFSuG3Llzw9TUFDY2NrC0tMSbN29SPd++fXtYWloCANq2bYsjR46gZ8+eOHz4MIYMGQIAMDU1RWBgIB48eIClS5di7dq1aNq0KfLnz4/g4GDUrVs3w3qlrHRUqlQJCQkJiIuLw/Hjx/HgwQN07dpV/dybN28QExODUaNGISQkBCtXrkRERASio6MRFxenfs7R0THTbfLq1SsMHz4cVlZW8PPzAwCEhYWp6+3m5oYff/wR/v7+CA8Ph4+PD0JCQmBpaYlixYrB1tY207IYhmEYAc9Hn5PRfAQA5cqVQ82aNdVtMnHiRLx9+xa5c+fOtByG+RQ2BHIIpqamqf5vbJx+1xsZGak/K5VKGBoaIiEhAREREShfvjwAoFu3bgCAUqVKYfbs2anyHzlyBK1bt86wXmZmZgAAAwMDtazk5GS0bdsWo0aNAgAkJycjOjoaefPmhZ+fH5KSktCyZUs0btwYUVFRUCqV6vIsLCwylAmIFabvv/8ezZo1g7+/v/p9Netdrlw5KBQKHDlyBMWLF4erqyv8/PxgbGzMuwEMwzBfCc9HqcnMfAQAhoapnTgMDAwybDuGyQh2DWLSZN++fUhISEB8fDx27twJV1dXhIWFwcnJKcO8SqUSFy5cUK9cZJX69evj77//Vm8Pb9q0Cb179wYABAcHY+jQoWjVqhUMDAxw6dIlJCUlZan8Bw8eoHfv3vj+++8xbtw49Y9uWvVu1qwZZs+ejfr166NUqVJ49+4d9uzZg+bNm3/VuzEMwzBZg+cjwa1bt3Djxg0AwJYtW1CrVi2Ym5t/1XsxTApsSjJpkitXLnTv3h2xsbFo3rw5OnTogIkTJ2YqfNmlS5dQuXLlVKs4WaFhw4YYMGAA+vbtCwMDA1hZWWHRokUwMDCAn58fhg4dirx588Lc3By1a9dOFWotM6xcuRIfPnzA+vXrsX79egBiheqnn376rN5ubm5YtWoV6tWrBwCoV68ebt26lanDaQzDMIz28HwkKFmyJBYtWoRHjx4hX758mDFjxle9E8NoYqDU3MdiGIhICmXKlEG/fv3+66owDMMwORiejxhGWnhHgPkm6d69O96/f5/mdxs3blSHamMYhmEYKeH5iMnO8I4AwzAMwzAMw2QT9uzZg6VLl0KhUMDHxwc9evRI8zl/f384OTnBy8vrq2XxYWGGYRiGYRiGyQY8e/YMc+fOxZ9//ondu3djy5YtuHPnzmfPDB48GPv379dantauQXfv3sWBAwfw9OlTGBoaws7ODg0bNkz3Ag2GYRiGYRiGySnExsYiNjb2s/Q8efIgT5486v+Hhoaibt26sLa2BgA0b94c+/fvh6+vr/qZPXv2oGnTpupntEErQ2Djxo3YunUrmjdvrlb8nz9/jgkTJqBNmzbo27dvlsortfSkNtXJFElRafvp6ZpDI7MWQuxrORJpmvFDOuB6jInkMvZujJFcBgAYX3wmi5zESvJcOFbGy15yGTXzxUsuI4Xpjk21ym9erFuq/394uEmr8pich2tQyH9dBYZh/mOOtaqvVf5P56JZo+ph0aJFnz3n6+urvq0aAKKjo1NdWGpnZ4fLly+nytO/f38AwPnz57WqI6ClIbBu3Trs2rXrszi2ffr0Qfv27bNsCNQur01tMkeuSpm74ENb2u+Ux+uqQ1V5FLS9G15LLqONt7XkMgBgzxt52sy6kZ0scm7clN7ovJEknxfh9MxfxpkmBgbs8cgwDMP8t3w6F/Xu3Rvt27f/7DnN3QAASOvobsold1KglSFgbGyMxMTEz9I/fvwIE5OsryD3LftOm+pkmoE7LSWX0aSaPDsC7oXlUWp3OUu/un3sDjDUMS7jB7XEZ548ERo6et/J+CEd4DeriCxyfj9nJoscbTEylGeXjGEYhmG+xKdz0acuQF/C3t4e4eHh6v9HR0fDzk66hUWtDIHBgwejXbt2cHZ2Vm9jPH/+HKdPn4afn1+Wy/vlYl5tqpMpNrm+Qljfz320dE394R8llwEA5YdbyyLH0kI6azSFUTXfSi4DALzGJ8giJ3+fMrLImdFpt+QyfNa1gGdlheRydIGhofRubAzDMAyTHl87F9WrVw8LFy7Eq1evYG5ujoMHD2LKlCk6rh2hlSHQunVr1KlTB2FhYYiOjoZSqYSjoyOGDRsGe/us+y37VpReEZx3TR7XIMPXb2SR411aHoNj6/VckssY5fdcchkAsON3G1nkdPB7IoscyybOkstwLSiP8aQLeEeAYRiG+a/52rnI3t4efn5+6NWrFxQKBTp27IiqVatiwIABGD58uM6D8WSrewT8zx2RXMaxCHncG1wd5HHZ2Tnitixy+i8rJbmMLdekNzYA4E1ghCxyLL0cZJEzvLb07lQh0fK5Bf3RsLFW+e3Kj0z1/+ibc7Qqj8l58GFhhmG0PSysL3NRtrpZePNR6WUYPXkhvRAAO1a9kkVOUjV5DqQuPmAkuYzi5eU55Hl0szxtVrX2KVnkTB2o3Y9VprgTI72MFBpql92QdwQYhmGY/xh9mYuylSHg0VAORTAvDlySXqmt7fWd5DIAoIiFPIeSN4dJ32YR9xIxy/OD5HKqLpDnj/PeRU9Z5Ljvl96lzqqcPO5UuoBdgxiGYZj/Gn2Zi7KVIeBkK70f8uSfX0ouAwCeFC0ui5ziVp9HbZICz9rJksvYt/0txi6RXAxgJ89h0g13omSRM7aq9MZgidzyGJy6wMiIDwszDMMw/y36MhdlK0Ng8UXpw3oaPbovuQwA2NtcnkO81QfKY9g07CP9pVV5a8qzi6JIkOdYzLo78px5qGYj/XmUHfvlixgUEaBdfn1ZhWEYhmG+XfRlLspWhsCgqtLf+lt8SzHJZQBAyDN5oqz0GS6Py8bqXyMll9FwcCHJZQBA8Ix7ssi53aKkLHJMy0v/Y1Ogsn78oAH645fJMAzDfLvoy1yUrQyBqV0vSS6j7VItry3NJB+TpI+7DwDHbkjvuw8AfUZJf6HY73vlibRkEifP6vbruWtkkdP9UFfJZay6Jc8lbLrAiO8RYBiGYf5j9GUuylaGQPeVtSSXMbSi9LsOADAszFoWOc5lpffdB4CN/0hv2daqJ4/x9NGpoixyEo/Is8PxNkH6dnv0UH/OCMBYnuhTDMMwDPNF9GQu0toQOHz4MJo1awYACAwMxMmTJ2FsbAw3Nze0atUqS2VtXip9yM1NMnWMhfR3PAEA+jnK44IUbiS9v7t/VelvfAaAAQcyvuJbF/zYW55twXkDpXd1KjS6suQydIVST358GYZhmG8XfZmLtDYEFi9ejGbNmmHhwoUIDw+Ht7c3lEoltmzZglu3bsHPzy/TZR2dL72y2XJrXsllAMCgOtKHwQQAE3kW0RH1S6DkMuY5dJBcBgAkxMtzWHh2kDwbbv+eqCm5jBW3YiSXoTP05MeXYRiG+YbRk7lIZ5rKoUOHEBgYCDMzcQNp48aN4enpmSVDYPhpa11V54s0qyBPuM2SMoVbHLLDQhY5edq7Sy7j3OR/JZcBAA0nlZFFTmKyPOc3KrW/IbkM70mFJZehM/Tkx5dhGIb5htGTuUhrQyAuLg4vXrxAoUKFEBcXpzYEPn78CGPjrBV/ed9rbauTIfeqyROicnRVeQwOgwR5DA6lofRbDwX95PHdl+uS3GUNpR/PAJBvi/Rj2nmU9JeWpRCwSLv8ShP9+PFlGIZhvl30ZS7S2hCoWbMm+vTpg6ioKPz8889YuHAhDh48iOnTp2PgwIFZKiupcG5tq5Mhq1rK44f+v7PyuCApTeVxc8lVSvq+ebJL+hClAJBURPp3AYDXdeTx22rjLf3ZmsHTeEeAYRiGYTKNnsxFWhsC06dPBwB8+PABL168AAA4ODhg2bJlKFeuXJbKMj35SNvqZIiPtYPkMgCgeBF5BsCaTvIYNhdeSh8Gq6y7PCEq19+Vx53qRJQ84VCTKuaXXMbUdpskl5HC6Htu2hWgxY/vnj17sHTpUigUCvj4+KBHjx5pPufv7w8nJyd4eXl9tSyGYRjmGyanGAKRkbSKa2RkhMjISFhZWam/K1Qo8yEUlyyWXqEJi5Ynys6Gs/JEjKnYUB4XpIH9n0kuo8tkeS57q5BXnjHw+x/yhKqFqfRnEexqNZFchs74yh/fZ8+eYe7cudixYwdMTU3RtWtXODk5oXTp0qmeCQgIQFhYGJycnHRVY4ZhGOZbI6cYAoMGDUJERATs7OygVKZ2UzEwMMCRI0cyXdbca9KHdYyTIeY6APg2kEcJXHfbXBY51/dWkVyG6+6PkssAAAOZ/jabdJYnatD35aUfa0aG1pLL0BWfhmyLjY1FbOznO2d58uRBnjz0mxMaGoq6devC2toaANC8eXPs378fvr6+6mf27NmDpk2bqp9hGIZhmLTIMeFDN23ahO7duyMgIAC1aml3IZh7IelDbi4ZHiG5DAD4rZmDLHIcnaQPuQoAvU7ESS5jV8sYyWUAQNNAeQ6M/9rinSxyomSIVNtqgzznKgAgwjfjZ9Llkx/ftWvXYtGiz08g+/r6YtiwYer/R0dHw9aWbtC2s7PD5cuXU+Xp378/AOD8+fNaVpJhGIb5pskphoCVlRWmTp2KwMBArQ2BbTKsbi9dL8+hx9q28kTzqVr7lCxyDFtUlVxGvX+tJZcBAMmno2SR41OwoCxy/ldZ+nMih7zlixqkNZ9Eaujduzfat2//2WOauwEAPtvRBMSuJsMwDMNkmZwSNQgAqlatiqpVtVcUn0+/nPFDWuLvJ72LCwAEtZMndKRpoQKyyEmwln7nYZyrPJewBcTbyyLn5Xt5lMgfT0ofoWq8k3yGQBktX+fT7dhPXYC+hL29PcLDw9X/j46Ohp2dnXaVYRiGYXIkOcY1SJck+lSSXIallTwdU2+NtSxy+k2X54zAyvXSuwYF7Jcn5KrRY3mU2pW9ZBGDhGTpZfx5V55xBgBti2tZwFeuwtSrVw8LFy7Eq1evYG5ujoMHD2LKlClaVoZhGIbJkeSUHYFTp05h//79ePr0KQwNDWFnZwcXFxc0b948y2UZHnygbXUyJKl3ScllAEBSkjzx/ZedlCc6kek96d1pto+V5ybetwp5/jg33DGTRc7VGOnHQH07eQ5y64KvvcTF3t4efn5+6NWrFxQKBTp27IiqVatiwIABGD58OKpUkWc3kWEYhtF/9OVCMQNlWo6xmWT+/Pm4fPky2rRpo95Cj46Oxt69e1G6dGn4+/tnqbyOR09+bVWyRH4z6f3377+TPu4+ANzeFS2LnAJu8rhIJMtgP9UrIk/40L0jbsoip8JUeRTUSTXeyCKnej5PrfKXGL031f/vz9KuPCbn4RoU8l9XgWGY/5hjreprlV9f5iKtdgSCgoKwb98+GBqmtno8PT3h6emZZUOgob30q467Hlji5UfpV55v+x+WXAYAhITVlEXO6/gYyWXsfCBPBKQ1fc7KIkfpU08WOUUtpb9LYt+CKHSQXIrgrpZ3lylluFeBYRiGYdJDX+YirQwBMzMzPH369LNLwyIjI2FqmnV3hQW/Sb/ieH2FteQyAGCQVWNZ5My8LIODOIBH76U/TlLdRp6beG3HNpRFTszGu7LIqeUhfXSimMHyRNvSCXqyHcswDMN8w+jJXKSVdjdmzBj06NEDDg4O6vjbL168wP379zF9+vQsl1fUK/O3EH8tBgbyWGjBsyNkkZPcwkEWOYb770kuY8rqfJLLAOQL7bu6pjwRnZ68l35M/1BJnjsRdIG++GUyDMMw3y76MhdpZQjUq1cPS5cuxdu3bxEdHY2IiAg8ffoUo0aNQt26dbNc3gJn6UNudjsmT2SaZDsLWeSc6SuP3/ZPVbUN5ZIxP5yW51zFvLryhHbd8Pd9WeQccZLePaxfOXlCu+oEE/3YjmUYhmG+YfRkLtLKEFizZg3Wr1+P5ORk1K1bF1FRUWjevDm2b9+O+/fvY+jQoVkqr2xe6VeENzYGbsS8lFyO1155ovms/leesI4PZHANMjNW4u7CO5LL6bBRnmg+G4LkiVDV2+uK5DIa/QLk8ZU+vC8AhHfVLr++xG5mGIZhvl30ZS7SSrvbvn07goKC8OLFC3h6euL06dMwMzNDp06d0LFjxywbAv2DpY/m8s9dAwAZXy6kLT8PkWcFdcZJeZTa872lP5DqvMkI5p1LSS6ntPQeaACAopYxssj551h5yWXU32IEhfRDQCcYmvBtwAzDMMx/i77MRVoZAsnJyTA1NUXhwoXRt29fmJmRUpqUlPUQnX3LvNemOpmiVj553E+mLJD+Ai4ASLaR57Dw+RfSx/XsX0ue++0qWcuj0TbqL8/FZYlVpd8V+ne0PK5uusDISD9+fBmGYZhvF32Zi7TSvNzd3dGzZ0+sW7cOw4YNAwDcvHkT48ePR8uWLbNc3ulo6ZX0nqXluRgptl9uWeQcj5LHNaiQhfR+9WHR8vzRrLljKYucv5bIY6R9Zyb97tPqf+V5FwAYXEG7/EbZ6r50hmEYJieiL3ORVtUcMWIEzp07ByMjOhBhamqKYcOGoVGjRlkuT45bcv+8KE+sej9neXYEClrIs7o96aL0hk0NG3ku+gr1Oy+LnD5j68gip0dF6cfawonyXFwHAIMDtctvrB/nsxiGYZhvGH2Zi7S2V2rXrp3q/yVLlkTJkl93SLJGRekPVoyvFiu5DADouEaelfqK1eQZadEvpXcNCr0mzwHrdkuryyJn1xp5lOe5V2Vw2yknT2hXXWBkrB/bsQzDMMy3i77MRVoZAn/++Se6d++OhIQELFmyBCdPnoSxsTGaNWuGvn37wtg4a8Vf3fRUm+pkCpMa8ijoHvXlGQDdSsoTPtR7ofTv0629PAefo+Lk2a9TWspzHqVoLSvJZbx5I70hqCuM9GQVhmEYhvl20Ze5SCuNKDAwEN27d8fMmTMRGxuLadOmQalUYuPGjQgICMC0adOyVJ4citP3J6wllwEAjx/I47LjbCfTAdtG0vvV/yN9VFcAwJ21j2SR4zFMngvFfq0t/U5a413ynRHQFn3ZjmUYhmG+XfRlLtKJFnnu3Dns2rULhoZCIZk6depXHRaeNFz61fqoOHnCejZqII+/e+e18uxwwED69zkyUPqoUQDgdkee+KH/RMnzK1B5pfRG56aO8kRA0gXGWoRs27NnD5YuXQqFQgEfHx/06NEj1fc3btzA+PHj8e7dOzg6OmLSpElZ3vlkGIZhvn30ZS7SagZ78+YNLl26hGLFiuHJkycoWrQoACAyMhImJllf3Y/+IP3K5omn8ijOy3+VZ3m7dHdrWeTc3/dcchk9DuaXXAYA5M4jj5vLdGd5zqOEPJN+J61cXj1Z2gDwtXr5s2fPMHfuXOzYsQOmpqbo2rUrnJycULp0afUzo0aNwtSpU1G9enWMGzcOW7duRffu3XVUc0Yb7t69iwMHDuDp06cwNDSEnZ0dGjZsiCpVqvzXVWMYJgeiL3ORVoaAl5cXli5diqtXr2Lq1KlYvnw5tm/fjl9//RVTpkzJcnlL5sVoU51MsWdOvOQyAKDe98dlkZNYroMsck7+Ir0i2LTvA8llAEBiFVtZ5PTv8UQWOTCS3oD+s0dZyWWkcNVHu/yfxm6OjY1FbOznRlmePHmQJw9dLhgaGoq6devC2toaANC8eXPs378fvr6+AIAnT57g48ePqF69OgDx+7dgwQI2BLIBGzduxNatW9G8eXO14v/8+XNMmDABbdq0Qd++ff/jGjIMk9PQl7lIK0MgpVIAEBcnQhieP38e+/btw3fffZfl8v6cLn30k9+uyvSiJQAAHDdJREFUyhND3rp7W1nkzO2pJ9e9ZoJC3g6yyHl09IUscpTfybP7NHmW9DspHxLlCYerCz71y1y7di0WLVr02XO+vr7q+08AIDo6Gra2ZCTa2dnh8uXLX/ze1tYWz54902HNma9l3bp12LVrF8zNU//N9enTB+3bt2dDgGEY2dGXuUgrQ2Ds2LGfpR09ehRKpXC9mD59epbKW3tHekPg4NBgyWUAQNeV9WSRY2ggzw6H67o8GT+kJfUqyWPUxDrayCLH0kWekJvHo6RvN3tz/TE4TY1Su3717t0b7du3/+w5zRUYAOrfLU0MDAwy/T3z32FsbIzExM/H6MePH7/KTZVhGEZb9GUu0soQsLa2xq5duzB48GD1i5w+fRp16nzdRUr/REn/gz1mkzyXPM04IL27BgCsWLxbFjn7QltLLqO3pzyuQRM3fd09F1nlp+XyKM8nZzpILqNCvVOSy0hhSlgzrfKbGqb+kfx02/VL2NvbIzw8XP3/6Oho2NnZpfr+xQvaTXr+/Hmq75n/jsGDB6Ndu3ZwdnZWr5Q9f/4cp0+fhp+f339cO4ZhciL6MhdpZQj4+/vDxcUF8+bNw48//ggnJyesXbs2TYsnM7xYfUeb6mSKbtvlOZA6c014xg/pgCl/eckip12jQ5LLMPdylVwGAPz1UIYLuABsGSVPpJ1x4dK7pyRW1R+F18Tw6w6D16tXDwsXLsSrV69gbm6OgwcPpjrrVLhwYZiZmeH8+fOoVasWdu3aBRcXF11Vm9GC1q1bo06dOggLC0N0dDSUSiUcHR0xbNgw2Nvb/9fVYxgmB6Ivc5HWce+cnZ1RoUIFBAQE4Pjx40hKSvrqslatlF7ZCH4mz1Z+62XOssjZeEOebW9FovRhV33ayXOh2A+V5LmE7dIrecJK7rwo/RhIrCSPAa0LPl2FySz29vbw8/NDr169oFAo0LFjR1StWhUDBgzA8OHDUaVKFcyePRvjx4/H+/fvUbFiRfTq1UvHtWe+Fnt7e7Rr1+6/rgbDMAwA/ZmLDJRpORt9JYGBgdi3bx/++OOPr8pfutMGXVXli4yYJM/K5l8P5TmUPL6aPErtwSfSK+mdSshzx0MBC3kux3oaJ497WC4ZInt23pNXeiEqLns31Cq/z8kTqf6/xqWRVuUxOQ/XoJD/ugoMw/zHHGtVX6v8+jIX6XTJslOnTujUqdNX509wLqzD2qTNnKPyKGcbO8XIIqfnNitZ5Hz3nfTttiVcpkN9v1+QRYzCq6Iscpq7SN9ufWp8lFyGrvjaVRiGYRiG0RX6MhdlqysxTS2kX9o0kumNfXbllkVOB0d5DqTu/Ed6l6rSJeUx0m47FZVFTq/m8rihbdgg/a7QsfCnkstIwU/Lc8mfRmpgGIZhGLnRl7lIa7X41KlT2L9/f6rbHF1cXNC8efMsl7WizTuMPy1tmMo3b5KR31Z6gyMmJhlvYqR3QWld7COORplKLuePdu+wX2L3oBJWifjV95GkMgDg2C57JMrgHdT5bzO8eiW9oKJN8iNi/DFJZRgOdoGp9MMMCQnal5FLT1ZhGIZhmG8XfZmLtDIE5s+fj8uXL6NNmzbq0EXR0dHYtm0bLl68CH9//yyV12+mAsBLbaqUIcXc5Dn0+FoGBRAA+kx4D+C95HLW2ZgDkNaH397JGvmGlJdUBgBYm76TXAYAWFgawMJSeqNzaYPXwPHqksqoXX25pOWnYoh2kXhM9GQVhmEYhvl20Ze5SCtDICgoCPv27YOhYWqXDk9PT3h6embZEEg8dkmb6mQKZbOmkssAAFmWnAEkF5X+oi8AMHwifSjMrc1fSy4DAHIZFZBFzvx60bLIGX9e+oO8Ube9JZehK/TFL5NhGIb5dtGXuUgrQ8DMzAxPnz5FoUKFUqVHRkbC9Cv8CLYdrqVNdTLFiFPydMwVX3lu/K3hdFUWOev3V5BcRuOR8hxITbaRR0G/OEmeMw9Rb6Q/izDrsny3s05z1C6/mZ78+DIMwzDfLvoyF2llCIwZMwY9evSAg4OD+jbHFy9e4P79+5g+fXqWy9t4V/qLnh4FSH8xFgC0M3eXRU65mXVlkdN7mPS3/nYbLc9K/dCKcbLIefxenh+BX5xjJZfRf4YOnPczidaGgAzhVBmGYRgmPfRlLtLKEKhXrx4mTZoEc3NzREdH4/Hjx3j69CkGDBiAunWzrqCGR0m/6lh8shueHn+R8YNa8nCT9IdeAaBIF3ki4ChqSH8754ZDSlz8UfpdgTot5YmAs3yD9OFwAcBniww3JZewQN58+vGrpi+RGhiGYZhvF32Zi7QyBKZNm4YbN25g7ty5CAkJwZUrV9CiRQucPHkS9+7dw/jx47NU3vNFN7SpTqZIrGYHGEnvSpGnhTxK4P1/5VmpLVPdXHIZ25vGApBe2cw3VHo3JwB48VGeQ8leztKfRzl43RhJifrxo6Yv27EMwzDMt4u+zEVaGQIhISHYs2cPjIyMcPz4cWzduhWmpqbo0qULPD09s1xeomNBbaqTKfp1yyW5DAC4GSvPYeEPBeS5GOH8DenvKzB1k+dytBer78giZ/xMeVyQZm4tIbmMK6+lv1laV+jLdizDMAzz7aIvc5FWWmSuXLnw8uVL2NnZIV++fIiLi4OpqSk+fPgAY+OsF925k/SrzkH35VFohlSVPqQnAGy4aymLnAIFpR/R5sa2kssAgMTHIbLI8VpeRxY5865KP6Yfb5T+jIialtpd664vqzAMwzDMt4u+zEVaGQK+vr7o2LEjPDw8ULJkSXh7e8PZ2RnBwcHo379/lsu7LMOqo7GJPLe9WpvKsyNwL0IeOba20kfA2X7/vuQyAMDE2kYWOdEf5VkOeHBa+sPCZk2LSC5DV5jpiV8mwzAM8+2iL3ORVoZAkyZNUKZMGRw+fBgPHjxA9erVYWlpiRkzZqBq1apZLs8+V5I21ckcuYCjF6UXM+m9PG4uyScfyyInpqn0Zx5+PmaB+JBnksupFSD9pWUAcGzoEVnkWOaWPtqSEoDZkMqSy9EFpjq2vyIjIzFq1Ci8fPkSJUqUwOzZs2FpmfZOXEhICFasWIG1a9fqthIMwzCMXqHruUgqtHYwL1q0KPr06aOLuiB4kfRK7f8m2aKum+Ri8Oi9PCNgvVOhjB/SAQa7pF+tX7bUFmguvavTwOnS3l6dgnGPhrLISbr6XHIZnf3sAMgXQlQbzHW8CjNp0iR0794dHh4eWLx4MZYsWYJRo0aleiY5ORlr1qzB8uXLUbZsWZ3KZxiGYfQPXc9FUqGVIXD48GE0a9YMABAYGIiTJ0/C2NgYbm5uaNWqVZbLGxYgvY/49L/lOVxbvkrWL1T7GgY2lOcSrhbd80suo2V9ee54eHKjpyxyyg9/KIuc/O2lDyH75zH5jIDpWt8joLsfX4VCgXPnzmHx4sUAAC8vL/Ts2fMzQ+Du3bu4e/cupkyZgvXr1+tMPsMwDKOf5AjXoMWLF6NZs2ZYuHAhwsPD4e3tDaVSiS1btuDWrVvw8/PLUnkxCdL7oQ9vLoP7EYAls+Rx2Qn8I58scu68kV5G3go1pBcCYOMd6e+RAAClkTw3Cy9wkb5z+sTmllyGrjD5pNljY2MRG/v5OYo8efIgT5486Zb1+vVrWFlZqYMf2Nra4tmzz93XypQpg2nTpuHMmTNfX3GGYRjmm+HTuSi7opPl8UOHDiEwMBBmZuKwb+PGjeHp6ZllQ2BlL+mjuRi3lyeSy+D/yaOgT7soz0grZCH9ZW92vUpKLgMAFobLY6Ubh/wri5xOG6tILuNYPxksQR1h/Ek8gLVr12LRokWfPefr64thw4ap/79v377PbkR3cHD4LJ+BgTwBBxiGYRj95dO5KLuilSEQFxeHFy9eoFChQoiLi1MbAh8/fvyq8KEjN9XTpjqZ4u5beVyDhlaUJ5rPwmvyyCmXV/qdlIJ55VHQbe2lvxMBAH47XVMWOYH3pb+4zG2cPG0GAPc+19mzhNEnIdt69+6N9u3bf/bcp7sBLVu2RMuWLVOlKRQKODk5ISkpCUZGRnj+/Dns7Oy0qyDDMAzzzfPpXJRd0UorrlWrFvr06YOoqCj8/PPPWLhwIQ4ePIjp06dj4MCBWS5v6cC72lQncyjkcQ1aeK6ZLHKuxjyVRc6yk9KfeWhQVR6jpoK1QhY5lcbJc5cE4qUf00vHyHMRny74dBUmMy5AX8LExASOjo4ICgpC69atsWvXLri4uOiglgzDMMy3TI7YEbCwsMD69ethZmaGFy+E37WDgwOWLVuGcuXKZbm8uVuKa1OdTFHYQh5DoKzLcVnk9J5fShY5p42ldw1aVl8eBb1GL3nOCEycLI972LEo6f33516TLw5aCy2vLDDS8Y9vQEAAxowZg6VLl6JgwYL47bffAACbNm1CdHQ0RowYoVuBDMMwjN6j67lIKgyUSuVX7104OjoiX758GDlyJNzd3bWuTM8TJ7QuIyNK5ZZH2ZTL4JjdS4ZdFADGg6WPIV+zlDzbaA/eyKPUznGWx6/+yivp3d2q5ZPPNcgxv4dW+e/E7kn1/9J5WmtVHpPzcA2S5/ZxhmGyL8daaXfLvb7MRVppEEWKFMHs2bMxceJErFy5En369EGTJk2QK9fXuRGcXvRIm+pkijMx8ZLLAICbB51kkbNmjPRx9wHg6aFoyWWUqfF17htZpVdpeVx2WtTbJ4uczms6SC7Dp6z0F8rpCn3ZjmUYhmG+XfRlLtLKEDAwMEDp0qWxYcMGhIaGYsuWLZg2bRocHBxQoEABzJkzJ0vlFejpoE11MsV291eSywCAeVejZJHz5KYsYrB5kpnkMnr6y9M3f1SS/k4EAFh2wFMWOU/ipF+td90rX9Sgk1oumsgUtZVhGIZhvoi+zEVaGQKaXkX16tVDvXr1oFAocOvWLTx6lPXV/YaFpV+t3/1AeoUWAJaNln53AwDO7ZRHqe12THp/d2UueXZrDN7KcznW2InyKM+G9QtKLqN0Cf2IfgDozyoMwzAM8+2iL3ORVoZAjx49PkszMTFB5cqVUbly1n3Ki1tK71e/4qKF5DIAINlWHpedBk0iZZHz3Y82kstILiBPmxnZmcsiZ3pvWcSgUcEYyWXU7/1Wchlq3Btold1YT0K2MQzDMN8u+jIXaWUIdOrUSVf1AAD0LSf9qvP6mx8klwEASkvpo+wAQOHx0l8mBQCPHkpvpL1aGyi5DAAoOUUeDb1ZYXl2Htofkv7vZslcee7f0AVGfOEXwzAM8x+jL3NRtprdx52T3pViewvpL18CAN+88rjslMr9URY5P1aWXql95NJZchkAYG4cJ4ucRlu+k0WOc0npI2ENniRPmwHAvRXa5Tc0yFY/awzDMEwORF/mIq1qmZycjK1bt2Lfvn149uwZDA0NYWdnBxcXF3h7e8PEJGur4l1LSb9aP/mC9DHXAcDKWJ4toT1X5Nl52HxA+su+Dg2T54zAmwR5rPQ3c6QPhwsAJ4bJcMGVnqxsAPrz48swDMN8u+jLXKRVLQMCApCcnIxhw4bBzs4OABAdHY3du3dj7NixmD17dpbK67hQ+vjus3rLo2wuuSGPwaFYf10WOcax0ofc9KnoKLkMAHCwkeeOB/ho5+ueWZIOSX8wvduoApLL0BWGkO/yM4ZhGIZJC32Zi7QyBM6dO4f9+/enSitWrBgcHR3h4ZH1S4Hm9pF+Ff12rDwW2sgqsbLIebJE+tuYAaBHaekH9IjT8lxadfSQPOdEDo+Ux+BYUU/6qEEFLOS7UExbDPRkFYZhGIb5dtGXuUirWlpZWeHy5cuoWrVqqvQLFy7AwiLr0Xk23pM+akz4IXminygtTWWRY5xPnnCofctJH23p2jN5zjtUaCDPbo37Ann86is5ST/W7r6VxwUNAIZV1C6/YfY6+sQwDMPkQPRlLtKqllOmTMHo0aMRHx8PW1tbAMCLFy9gamqKX3/9NcvlXVgr/SVcRgCsWxSSXA4AxOyXPrTnuVHyhML8kCj9KvrBNkDnY9Ibg8lK4Lc6MZLLOVVUHmOwnn2MLHIuvZLPGNAGffHLZBiGYb5d9GUu0qqWFSpUwPDhw7F+/XoYGxsjKSkJNWvWROfOnVG+fPmsF5ggvSuFefOiiJfhmEA/x49AFelj79f8RR73k+R8uSSXUauiISyMpHcPG1rhLaLipL/yb8UFeYy0Wm7SRw2ac1WeXRQA8C6tXX4DA/3wy2QYhmG+XXQ9F0VGRmLUqFF4+fIlSpQogdmzZ8PSMu3F05CQEKxYsQJr167NsFytDIHly5fj0qVLaNGiBY4ePYo6deogV65cmDBhAnr16oXOnbMWDjKxiq021ckUPWvI435S106eGPKGneVZpf39vPSKc0KyPJFphvR7Koscj4nSG08AUN5aejmnr8l4MYqrdtn1ZTuWYRiG+XbR9Vw0adIkdO/eHR4eHli8eDGWLFmCUaNGpXomOTkZa9aswfLly1G2bNlMlatVLYOCgrBz504YGhqiQ4cOGDBgANatW4cOHTqgc+fOWTYEIH2ESux/LM/Nwss3yhOdCAp5Dr6anLknuYxnwytJLgMAFM6FZZHzcw157qxod1j6C8XwVJ7D77pAX7ZjGYZhmG+XT+ei2NhYxMZ+PpfmyZMHefLkSbcshUKBc+fOYfHixQAALy8v9OzZ8zND4O7du7h79y6mTJmC9evXZ6qeWs2Y8fHx+PjxIywsLPDx40fExMQAACwsLGBomPUV5Afj3bSpTvYi60GTGOarONJSBiFyyNARhgbyGJTMt8uxVvX/6yowDKPnfDoXrV27EIsWLfrsOV9fXwwbNizdsl6/fg0rKysYGwu13dbWFs+ePfvsuTJlymDatGk4c+ZMpuuplSHg5eWFbt26oUGDBggODoaXlxeePHmCoUOHwtPTU5uiGYZhGIZhGOaboHfv3mjfvv1n6Z/uBuzbtw/Tp09Plebg4PBZPgMdXfSplSEwcOBAVKlSBdevX8eYMWPg7OyM9+/fY+bMmShXrpxOKsgwDMMwDMMw+kxmXIAAoGXLlmjZMvU2vEKhgJOTE5KSkmBkZITnz5+rL/LVFq2daZ2dneHs7Kz+v6WlJRsBDMMwDMMwDKMDTExM4OjoiKCgILRu3Rq7du2Ci4uLTsqWPhQMwzAMwzAMwzBfTUBAALZu3YpWrVohPDwcP/zwAwBg06ZNmD9//leXa6BUKmWMC8gwDMMwDMMwTHaAdwQYhmEYhmEYJgfChgDDMAzDMAzD5EDYEGAYhmEYhmGYHAgbAgzDMAzDMAyTA2FDgGEYhmEYhmFyIHptCOzZswetWrWCm5sbNm7cKJmcd+/ewdPTE48fP5ZMxqJFi+Dh4QEPDw/MmjVLMjnz589Hq1at4OHhgdWrV0smBwBmzpyJMWPGSFZ+r1694OHhgbZt26Jt27a4dOmSJHKOHj0KLy8vtGjRAlOnTpVERmBgoPo92rZti1q1amHy5Mk6l7N79271OJs5c6bOy09hxYoVaN68OVq3bo2lS5dKJodhsgM8F2UdnouyDs9FWYfnokyg1FOePn2qdHV1Vb5+/Vr5/v17ZevWrZW3b9/WuZyLFy8qPT09lZUqVVI+evRI5+UrlUplSEiIskuXLsr4+HhlQkKCslevXsqDBw/qXM6ZM2eUXbt2VSoUCuWHDx+Urq6uyrt37+pcjlKpVIaGhiqdnJyU/v7+kpSfnJysrF+/vlKhUEhSfgoPHz5UNmjQQBkVFaVMSEhQduvWTXn8+HFJZf77779KNzc35cuXL3VablxcnLJ27drKly9fKhUKhbJjx47KkJAQncpQKsV49vT0VL59+1aZmJioHDRokPLAgQM6l8Mw2QGei7IOz0VZh+eirMNzUebQ2x2B0NBQ1K1bF9bW1rCwsEDz5s2xf/9+ncvZunUrAgICdHaVc1rY2tpizJgxMDU1hYmJCUqVKoXIyEidy6lTpw7WrVsHY2NjvHz5EklJSbCwsNC5nJiYGMydOxeDBw/Wedkp3Lt3DwYGBhgwYADatGmDDRs2SCLn0KFDaNWqFQoUKAATExPMnTsX1apVk0RWChMnToSfnx9sbGx0Wm5SUhKSk5Px4cMHJCYmIjExEWZmZjqVAQDXr19HgwYNYGVlBSMjIzRs2BCHDx/WuRyGyQ7wXJR1eC7KOjwXZR2eizKH3hoC0dHRsLW1Vf/fzs4Oz54907mcadOmwdHRUeflalKmTBlUr14dABAREYGgoCA0atRIElkmJiZYsGABPDw84OzsDHt7e53L+Pnnn+Hn54c8efLovOwUYmNj4ezsjMWLF2PNmjXYvHkzQkJCdC7nwYMHSEpKQr9+/dCmTRv8+eefyJs3r87lpBAaGoqPHz+iZcuWOi/bysoKI0aMQMuWLeHi4oLChQujZs2aOpdTqVIlBAcHIyYmBvHx8Th69ChevHihczkMkx3guejr4Lkoa/BclHV4LsocemsIKNO4ENnAwOA/qInuuH37Nvr27Qt/f384ODhIJmf48OEICwtDVFQUtm7dqtOyAwMDUbBgQTg7O+u03E+pUaMGZs2aBQsLC9jY2KBjx444ceKEzuUkJSUhLCwMv/76K7Zu3YorV65g586dOpeTwubNm9GnTx9Jyr558ya2b9+OY8eOITg4GIaGhli1apXO5Tg7O8PLywve3t7o378/atWqBRMTE53LYZjsAM9FXw/PRZmH56Ksw3NR5tBbQ8De3j6VZRcdHS3plqnUnD9/Hj4+Phg5ciTat28viYy7d+/ixo0bAABzc3O4u7vj1q1bOpURFBSEkJAQtG3bFgsWLMDRo0fxyy+/6FQGAISHhyMsLEz9f6VSCWNjY53LyZ8/P5ydnWFjY4NcuXKhadOmuHz5ss7lAEBCQgLOnTuHJk2aSFJ+cHAwnJ2dkS9fPpiamsLLywtnz57VuZx3797Bzc0Ne/bswfr162Fubo6iRYvqXA7DZAd4Lso6PBdlHZ6Lsg7PRZlDbw2BevXqISwsDK9evcKHDx9w8OBBuLi4/NfV+iqioqIwdOhQzJ49Gx4eHpLJefz4McaPH4+EhAQkJCTgyJEjqFWrlk5lrF69Gnv37sXu3bsxfPhwNGnSBOPGjdOpDAB4+/YtZs2ahfj4eLx79w47d+6Em5ubzuW4uroiODgYsbGxSEpKwqlTp1CpUiWdywGAW7duwcHBQRJfWQAoX748QkNDERcXB6VSiaNHj6JKlSo6l/P48WMMHToUiYmJePv2LQIDAyXZXmaY7ADPRVmH56Ksw3NR1uG5KHPo3myVCXt7e/j5+aFXr15QKBTo2LEjqlat+l9X66tYtWoV4uPjMWPGDHVa165d0a1bN53KadSoES5duoR27drByMgI7u7ukv7YS4mrq6v6XZKTk9G9e3fUqFFD53KqVauG/v37o3v37lAoFKhfvz46dOigczkA8OjRIxQoUECSsgGgQYMGuH79Ory8vGBiYoIqVapg4MCBOpdTvnx5uLu7o02bNkhKSoKPj4/OJ3mGyS7wXJR1eC7KOjwXZR2eizKHgTItB0eGYRiGYRiGYb5p9NY1iGEYhmEYhmGYr4cNAYZhGIZhGIbJgbAhwDAMwzAMwzA5EDYEGIZhGIZhGCYHwoYAwzAMwzAMw+RA2BBgGIZhGIZhmBwIGwIMwzAMwzAMkwP5P+fHp0vfhLAmAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "\u003cFigure size 864x432 with 12 Axes\u003e"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "sns.set_theme()\n",
        "\n",
        "def plot_params(params):\n",
        "  fig, axs = plt.subplots(ncols=2, nrows=3)\n",
        "  fig.tight_layout()\n",
        "  fig.set_figwidth(12)\n",
        "  fig.set_figheight(6)\n",
        "  for row, module in enumerate(sorted(params)):\n",
        "    ax = axs[row][0]\n",
        "    sns.heatmap(params[module][\"w\"], cmap=\"YlGnBu\", ax=ax)\n",
        "    ax.title.set_text(f\"{module}/w\")\n",
        "\n",
        "    ax = axs[row][1]\n",
        "    b = np.expand_dims(params[module][\"b\"], axis=0)\n",
        "    sns.heatmap(b, cmap=\"YlGnBu\", ax=ax)\n",
        "    ax.title.set_text(f\"{module}/b\")\n",
        "\n",
        "plot_params(params)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5P0pEpPi4404"
      },
      "source": [
        "To train our network we'll create some simple synthetic batches of data:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3asQPLfy4405",
        "outputId": "67800bed-daed-47d3-9abc-89fccb56132f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "x := [[0.0], [8.0], [7.0], [1.0]] y := [0 8 7 1]\n",
            "x := [[6.0], [7.0], [0.0], [9.0]] y := [6 7 0 9]\n",
            "x := [[4.0], [0.0], [9.0], [6.0]] y := [4 0 9 6]\n",
            "x := [[0.0], [4.0], [6.0], [5.0]] y := [0 4 6 5]\n",
            "x := [[4.0], [3.0], [0.0], [5.0]] y := [4 3 0 5]\n"
          ]
        }
      ],
      "source": [
        "def dataset(*, batch_size, num_records):\n",
        "  for _ in range(num_records):\n",
        "    y = np.arange(num_classes)\n",
        "    y = np.random.permutation(y)[:batch_size]\n",
        "    x = y.reshape([batch_size, 1]).astype(np.float32)\n",
        "    yield x, y\n",
        "\n",
        "for x, y in dataset(batch_size=4, num_records=5):\n",
        "  print(\"x :=\", x.tolist(), \"y :=\", y)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_V-7A7bO4405"
      },
      "source": [
        "Now for the interesting part. Lets pretend that we only want to update the parameters of the first and last layer of our MLP.\n",
        "\n",
        "The simplest and most efficient way to do this is to partition our parameters into two groups, \"trainable\" and \"non trainable\". Haiku provides a convenience function for doing this in `hk.data_structures.partition(..)`:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "344G-XSp4406",
        "outputId": "1a1e2c03-f6fc-463d-f8e0-a14a86c13d19"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "trainable: ['mlp/~/linear_0', 'mlp/~/linear_2']\n",
            "non_trainable: ['mlp/~/linear_1']\n"
          ]
        }
      ],
      "source": [
        "# Partition our params into trainable and non trainable explicitly.\n",
        "trainable_params, non_trainable_params = hk.data_structures.partition(\n",
        "    lambda m, n, p: m != \"mlp/~/linear_1\", params)\n",
        "\n",
        "print(\"trainable:\", list(trainable_params))\n",
        "print(\"non_trainable:\", list(non_trainable_params))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1PBAtp474406"
      },
      "source": [
        "The reason we split our parameters is that this allows us to pass them to our loss function as separate positional arguments.\n",
        "\n",
        "In JAX gradients are taken with respect to positional arguments. By splitting our parameters into two groups we can take gradients with respect to just one of the positional arguments. We can then use those gradients to update a subset of our parameters.\n",
        "\n",
        "The last piece of the puzzle is that we need to combine our \"trainable\" and \"non trainable\" parameters together before calling our apply function. Again Haiku provides `hk.data_structures.merge(..)` to make this easy:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "cixwKd854407"
      },
      "outputs": [],
      "source": [
        "def loss_fn(trainable_params, non_trainable_params, images, labels):\n",
        "  # NOTE: We need to combine trainable and non trainable before calling apply.\n",
        "  params = hk.data_structures.merge(trainable_params, non_trainable_params)\n",
        "\n",
        "  # NOTE: From here on this is a standard softmax cross entropy loss.\n",
        "  logits = f.apply(params, None, images)\n",
        "  labels = jax.nn.one_hot(labels, logits.shape[-1])\n",
        "  return -jnp.sum(labels * jax.nn.log_softmax(logits)) / labels.shape[0]\n",
        "\n",
        "def sgd_step(params, grads, *, lr):\n",
        "  return jax.tree.map(lambda p, g: p - g * lr, params, grads)\n",
        "\n",
        "def train_step(trainable_params, non_trainable_params, x, y):\n",
        "  # NOTE: We will only compute gradients wrt `trainable_params`.\n",
        "  trainable_params_grads = jax.grad(loss_fn)(trainable_params,\n",
        "                                             non_trainable_params, x, y)\n",
        "\n",
        "  # NOTE: We are only updating `trainable_params`.\n",
        "  trainable_params = sgd_step(trainable_params, trainable_params_grads, lr=0.1)\n",
        "  return trainable_params\n",
        "\n",
        "train_step = jax.jit(train_step)\n",
        "\n",
        "for x, y in dataset(batch_size=num_classes, num_records=10000):\n",
        "  # NOTE: In our training loop only our trainable parameters are updated.\n",
        "  trainable_params = train_step(trainable_params, non_trainable_params, x, y)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KLnpQFde4407"
      },
      "source": [
        "We can see that even though we only trained a subset of our parameters, our NN is able to learn this simple function:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "zjdRHp9Y4408",
        "outputId": "47e4d406-fb5d-46af-8280-0b121ef5a00d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "after training\n",
            "[0.] -\u003e 0\n",
            "[1.] -\u003e 1\n",
            "[2.] -\u003e 2\n",
            "[3.] -\u003e 3\n",
            "[4.] -\u003e 4\n",
            "[5.] -\u003e 5\n",
            "[6.] -\u003e 6\n",
            "[7.] -\u003e 7\n",
            "[8.] -\u003e 8\n",
            "[9.] -\u003e 9\n"
          ]
        }
      ],
      "source": [
        "# Merge params again for inference.\n",
        "params = hk.data_structures.merge(trainable_params, non_trainable_params)\n",
        "\n",
        "print(\"after training\")\n",
        "test(params)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Vj8Fjh9B4408"
      },
      "source": [
        "Of course it is not smart enough to generalize to out of distribution inputs:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ISkLKd9M4408",
        "outputId": "9f889a5c-e43f-48cb-ff90-0c9280591e8a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[0.] -\u003e 0\n",
            "[1.] -\u003e 1\n",
            "[2.] -\u003e 2\n",
            "[3.] -\u003e 3\n",
            "[4.] -\u003e 4\n",
            "[5.] -\u003e 5\n",
            "[6.] -\u003e 6\n",
            "[7.] -\u003e 7\n",
            "[8.] -\u003e 8\n",
            "[9.] -\u003e 9\n",
            "[10.] -\u003e 9\n",
            "[11.] -\u003e 9\n",
            "[12.] -\u003e 9\n",
            "[13.] -\u003e 9\n",
            "[14.] -\u003e 9\n",
            "[15.] -\u003e 9\n",
            "[16.] -\u003e 9\n",
            "[17.] -\u003e 9\n",
            "[18.] -\u003e 9\n",
            "[19.] -\u003e 9\n"
          ]
        }
      ],
      "source": [
        "test(params, num_classes=num_classes+10)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eDvlHZmi4409"
      },
      "source": [
        "Looking at our parameters we can see that `linear_1` is still in its initial state (randomly initialised weight matrix and zero initialized bias):"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "H4ZjlWEM4409",
        "outputId": "074c8837-f50c-474d-d3bd-e36587b641c7"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "\u003cFigure size 864x432 with 12 Axes\u003e"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "plot_params(params)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WprCXgMa5UZv"
      },
      "source": [
        "## Freezing layers with Optax\n",
        "\n",
        "Alternatively, [Optax](https://github.com/deepmind/optax) users can fix parameters using [`optax.multi_transform`](https://optax.readthedocs.io/en/latest/api.html#optax.multi_transform). Users can read more [here](https://github.com/google/flax/discussions/1453).\n",
        "\n"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "non_trainable.ipynb",
      "provenance": []
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}
